US20070209070A1 - Integrated network intrusion detection - Google Patents

Integrated network intrusion detection Download PDF

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Publication number
US20070209070A1
US20070209070A1 US11/702,908 US70290807A US2007209070A1 US 20070209070 A1 US20070209070 A1 US 20070209070A1 US 70290807 A US70290807 A US 70290807A US 2007209070 A1 US2007209070 A1 US 2007209070A1
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application
network
monitoring
invoked
intrusion
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US11/702,908
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Satyendra Yadav
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Intel Corp
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Intel Corp
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Priority to US11/702,908 priority Critical patent/US20070209070A1/en
Assigned to INTEL CORPORATION reassignment INTEL CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: YADAV, SATYENDRA
Publication of US20070209070A1 publication Critical patent/US20070209070A1/en
Priority to US12/649,018 priority patent/US8752173B2/en
Priority to US14/300,420 priority patent/US9143525B2/en
Priority to US14/861,232 priority patent/US10044738B2/en
Priority to US15/982,318 priority patent/US10771484B2/en
Abandoned legal-status Critical Current

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416Event detection, e.g. attack signature detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/02Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/02Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
    • H04L63/0227Filtering policies
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1425Traffic logging, e.g. anomaly detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441Countermeasures against malicious traffic
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441Countermeasures against malicious traffic
    • H04L63/145Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/20Network architectures or network communication protocols for network security for managing network security; network security policies in general
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/02Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
    • H04L63/0209Architectural arrangements, e.g. perimeter networks or demilitarized zones
    • H04L63/0218Distributed architectures, e.g. distributed firewalls

Definitions

  • the present application describes systems and techniques relating to network intrusion detection, for example, integrated network intrusion detection.
  • a machine network is a collection of nodes coupled together with wired and/or wireless communication links, such as coax cable, fiber optics and radio frequency bands.
  • a machine network may be a single network or a collection of networks (e.g., an internetwork), and may use multiple networking protocols, including internetworking protocols (e.g., Internet Protocol (IP)). These protocols define the manner in which information is prepared for transmission through the network, and typically involve breaking data into segments generically known as packets (e.g., IP packets, ATM (Asynchronous Transfer Mode) cells) for transmission.
  • IP Internet Protocol
  • IP Internet Protocol
  • IP Internet Protocol
  • packets e.g., IP packets, ATM (Asynchronous Transfer Mode) cells
  • a node may be any machine capable of communicating with other nodes over the communication links using one or more of the networking protocols.
  • networking protocols are typically organized by a network architecture having multiple layers, where each layer provides communication services to the layer above it.
  • a layered network architecture is commonly referred to as a protocol stack or network stack, where each layer of the stack has one or more protocols that provide specific services.
  • the protocols may include shared-line protocols such as in Ethernet networks, connection-oriented switching protocols such as in ATM networks, and/or connectionless packet-switched protocols such as in IP.
  • Encapsulation enables data to travel from a source process on one node to a destination process on another node, through multiple networks using different protocols and addressing schemes, without the two end nodes knowing anything about the intermediate addressing schemes and protocols.
  • Machine networks may provide powerful communication capabilities, but also may increase the difficulty of maintaining computer system security by making systems and data more accessible. Most networks are susceptible to attacks or improper use, both from inside and unauthorized access to data, destroy or bring down a computer system, prevent others from accessing a system and attempts to take control of a system. For example, some network intrusions exploit application anomalies to gain access to a system and infect it with a computer virus, such as Code Red or Nimba.
  • a common technique used to improve network security is to install a firewall, which restricts and controls the flow of traffic between networks, typically between an enterprise network and the Internet.
  • Firewalls typically monitor incoming and outgoing traffic and filter, redirect, repackage and/or discard packets.
  • a firewall may serve as a proxy and may enforce an organization's security policies.
  • NID network intrusion detection
  • Traditional network intrusion detection (NID) systems attempt to examine every packet on a network in order to detect intrusions.
  • NFR Network Flight Recorder
  • These NID systems may be implemented as standalone systems (e.g., NFR (Network Flight Recorder), provided by Cisco Systems, Inc. of San Jose, Calif.), or they may be implemented as distributed node-based systems (e.g., BlackICE, provided by Network Ice Corporation of San Mateo California).
  • FIG. 1 is a combined flowchart and state diagram illustrating a method of monitoring network traffic to detect intrusions.
  • FIG. 2A is a block diagram illustrating a system implementing integrated network intrusion detection.
  • FIG. 2B is a block diagram illustrating another system implementing integrated network intrusion detection.
  • FIG. 3 is a combined flowchart and state diagram illustrating a method of servicing network requests in an application rule enforcer component of an integrated network intrusion detection system.
  • FIG. 4 is a combined flowchart and state diagram illustrating a method of filtering network communications in a network traffic enforcer component of an integrated network intrusion detection system.
  • FIG. 5A is a combined flowchart and state diagram illustrating a method of detecting intrusion preludes and intrusions in a first detector component of an integrated network intrusion detection system.
  • FIG. 5B is a combined flowchart and state diagram illustrating a method of detecting intrusions in a second detector component of an integrated network intrusion detection system.
  • FIG. 6 is a block diagram illustrating an example data processing system.
  • the systems and techniques described here relate to integrated network intrusion detection.
  • the description that follows frequently discusses intrusion detection in the context of IP networks, but the systems and techniques described apply equally to multiple types of machine communication networks and operating system environments.
  • the term “application” means a software program, which is a collection of computing operations embodied by a set of instructions (e.g., one or more binary objects, one or more scripts, and/or one or more interpretable programs).
  • component means a software program designed to operate with other components and/or applications.
  • process means an executing software program.
  • execution context means a set of processing cycles given to a process, such as a task in a multitasking operating system. Both an invoked application and an invoked component are a separate process, even if their functionality is interrelated and they share a single execution context. For example, an applet and a Web browser in which the applet runs are each a process.
  • application means a component designed specifically to be run from within an application.
  • thread means a part of a software program that is given its own execution context.
  • intrusion means an attempt to break into and/or misuse a computing system.
  • intrusion prelude means communication activities that typically precede an intrusion.
  • intrusion signature means a communication pattern identified as corresponding to a known type of intrusion, including patterns that may be found in individual packets and patterns that may be gleaned from analyzing multiple packets.
  • the present inventor recognized the potential advantages of integrating firewall filtering information with network intrusion analysis.
  • most network traffic is legitimate and only a small portion of network communications may contain intrusions.
  • intrusion preludes may be detected (including detection using fabricated responses to blocked network requests), and particular sources of network communications may be singled out for greater scrutiny.
  • an overall amount of network traffic that needs to be monitored may be reduced, real-time intrusion detection may be improved, and more information about an intruder and the intruder's system and/or network may be obtained.
  • firewall functionality may be integrated with intrusion detection on end nodes (e.g., servers and hosts) in a network, such as an enterprise network, to further improve intrusion detection and network security.
  • end nodes e.g., servers and hosts
  • a networked machine may include an intrusion detection system that functions in part as a dynamic firewall for the networked machine.
  • the intrusion detection system may include three components.
  • the first component may be an application rule enforcer that authorizes network service requests from applications invoked on the networked machine and identifies abnormal behavior by an invoked application.
  • the second component may be a network traffic enforcer that monitors inbound network communications and blocks those communications that fail to correspond to an authorized network service request.
  • the third component may be an intrusion detector that monitors the blocked communications and identifies abnormal application behavior to determine when additional traffic monitoring is needed to detect an intrusion. Thus, the total number of communications (e.g., packets) that are examined may be reduced while intrusions may be detected more effectively.
  • FIG. 1 is a combined flowchart and state diagram illustrating a method of monitoring network traffic to detect intrusions.
  • the method begins by identifying one or more applications invoked on a machine ( 100 ). This identification may be performed for an application by examining network communications generated by the application, system records for the application, and/or a set of instructions embodying the application.
  • a default state 105 is entered, in which inbound traffic (i.e., inbound network communications) and traffic corresponding to a watch list are monitored. These network communications are monitored to detect an intrusion prelude or an intrusion. Moreover, multiple levels of monitoring may be implemented in the default monitoring state 105 .
  • inbound traffic i.e., inbound network communications
  • traffic corresponding to a watch list are monitored. These network communications are monitored to detect an intrusion prelude or an intrusion.
  • multiple levels of monitoring may be implemented in the default monitoring state 105 .
  • the new application When a new application is invoked, the new application is identified ( 100 ).
  • a request is received for network service (i.e., a network input/output (I/O) request) from an invoked application, a check is made as to whether the request violates a network policy ( 110 ).
  • the network policy may include a system policy and/or an application-specific policy.
  • the request may include information such as destination IP address, destination port, source port and type of request (e.g., bind, connect, accept, listen, send, receive, etc.).
  • the network policy may also include restrictive rules that specify communications that are not allowed (e.g., a Deny action).
  • the request is designated as authorized ( 115 ). Then, a communication channel for the request is enabled ( 120 ), and monitoring continues.
  • Rules similar to the policy rule above may be dynamically added to and removed from a network filter driver to open and close communication channels. Such filtering rules identify authorized network flows associated with invoked applications.
  • a channel may be created by specifying an open channel for a network flow using five values: (1) source IP address, (2) source port, (3) destination IP address, (4) destination port, and (5) protocol. Additional and/or alternative values may be used to specify an open channel.
  • inbound traffic that corresponds to the open channel is allowed, whereas inbound traffic that fails to correspond to an open channel is blocked in the monitoring state 105 .
  • outbound traffic may also be monitored in the monitoring state 105 , and disabled channels may also be created, such as by using the Deny action discussed above.
  • Blocked traffic is monitored to detect an intrusion prelude, for example, a system scan, a port scan and/or an operating system (OS) fingerprinting.
  • the blocked traffic may be checked for patterns that span multiple communications and/or multiple communication channels (e.g., multiple TCP/IP (Transmission Control Protocol/Internet Protocol) connections).
  • TCP/IP Transmission Control Protocol/Internet Protocol
  • a source of the intrusion prelude is identified ( 125 ). For example, a source IP addresses may be extracted from a packet that is part of the intrusion prelude. This source is then added to a watch list for increased monitoring ( 130 ), and monitoring continues. All packets from the identified source may then be monitored and these packets may be checked for intrusion signature(s). Additionally, multiple sources may be associated with each other, both in intrusion prelude detection and in subsequent intrusion detection, to counter distributed attacks.
  • the request is designated as unauthorized ( 135 ).
  • a determination is then made as to whether the application that generated the unauthorized request is behaving abnormally ( 140 ). This determination may be based on the number of unauthorized requests and/or on the severity of the unauthorized request generated by the application. For example, in one implementation, a single unauthorized request may be treated as abnormal behavior by an application. If the requesting application is behaving normally, monitoring continues.
  • a level of monitoring for the application is increased ( 145 ), and monitoring continues.
  • the application may be added to a watch list to initiate monitoring of network communications both to and from the application. This monitoring may include searching packets for application-specific intrusion signatures.
  • FIG. 2A is a block diagram illustrating a system implementing integrated network intrusion detection.
  • a networked machine 200 includes a network stack, which is a set of layered software modules implementing a defined protocol stack. The number and composition of layers in the network stack will vary with machine and network architecture, but generally includes a network driver 205 , a network transport layer 210 (e.g., TCP/IP) and an application layer 220 .
  • a network driver 205 e.g., TCP/IP
  • an application layer 220 e.g., IP
  • An intrusion detection system (IDS) 230 may be implemented between the network driver 205 and the network transport layer 210 so that all incoming packets may be monitored. Packet-level intrusion detection may be implemented in an NDIS (Network Driver Interface Specification) intermediate driver in a Windows environment. In addition, the IDS 230 may have additional components 232 placed elsewhere in the network stack. System-level intrusion detection may be implemented in one or more TDI (Transport Driver Interface) filter drivers, and application-level intrusion detection may be implemented in one or more components placed just below and/or just inside the application layer 220 (i.e., as part of a network interface library).
  • TDI Transport Driver Interface
  • an application-level component 234 is used as part of the IDS 230 , network services requested by applications 224 go to the application-level component 234 first. As a result, the application-level component 234 knows which application requested which network service.
  • the application-level component 234 may be implemented as a WinSock (Windows Socket) Layer Service Provider (LSP) and/or as a TDI filter driver.
  • WinSock is an Application Programming Interface (API) for developing Windows programs that communicate over a network using TCP/IP.
  • application-level components 236 may be used for intrusion detection. Such components 236 load and run with each new network application 224 in an execution context 222 for that network application. These components 236 may perform authorization of network requests and application-specific intrusion signature detection such that the processing time consumed by these techniques affects only corresponding network applications.
  • the networked machine 200 is coupled with a network 240 that may provide communication links to a security operation center 242 and a potential intruder 244 .
  • the security operation center 242 may include a central security server.
  • Various alert levels may be used in the IDS 230 . These alert levels may trigger heightened monitoring states, cause alerts to be sent to the security operation center 242 , and/or initiate logging of network activity, locally and/or with the central security server, for later forensic analysis.
  • the IDS 230 functions as a dynamic firewall for the networked machine 200 .
  • the IDS 230 monitors network traffic to block traffic that violates a network policy and monitors blocked traffic to detect an intrusion prelude.
  • the IDS 230 monitors traffic from the potential intruder 244 when an intrusion prelude is detected.
  • the IDS 230 may track behavior of applications 224 using a network policy that specifies behavior criteria (which may be application-specific) to identify abnormal application behavior.
  • the IDS 230 may monitor traffic from an abnormally behaving application 224 a to identify an intrusion, including e.g. an intrusion connected with a Trojan Horse in the application.
  • FIG. 2B is a block diagram illustrating a system implementing integrated network intrusion detection.
  • a networked machine 250 includes a network stack, as described above, and generally includes a network driver 255 , a network transport layer 260 (e.g., TCP/IP) and an application layer 270 .
  • the networked machine 250 also includes an intrusion detection system divided into three components: an intrusion detector 280 , a network traffic enforcer 282 , and an application rule enforcer 284 .
  • these components 280 , 282 , 284 may reside in fewer or greater than three software modules.
  • the intrusion detector 280 may include a kernel component that resides in a first module with the network traffic enforcer 282
  • the intrusion detector 280 also may include a user component that resides in a second module with the application rule enforcer 284 .
  • the application rule enforcer 284 may be a component that is invoked separately with each of multiple invoked applications 274 , as described above.
  • the networked machine 250 is coupled with a network 290 that may provide communication links to a central security server 292 and a potential intruder 294 .
  • the request is either authorized or rejected by the application rule enforcer 284 . If the request is authorized, corresponding authorized communications 272 are allowed to pass from the application 274 to the network 290 , and from the network 290 to the application 274 . If a request is rejected, this rejected request is communicated to the intrusion detector 280 .
  • the intrusion detector 280 may determine that an application 274 a is behaving abnormally, and the intrusion detector 280 may then begin monitoring other communications 278 for the suspect application 274 a .
  • This additional monitoring of communications 278 may involve checking for application-specific intrusion signatures, which may be dynamically loaded from the central security server 292 .
  • the network traffic enforcer 282 monitors incoming network traffic. If an inbound communication 262 fails to correspond to an authorized request (i.e., the inbound communication was not effectively pre-approved by the application rule enforcer), the communication is dropped (i.e., blocked from passage to another layer in the network stack). Additionally, the network traffic enforcer 282 may monitor outbound communications in a similar manner. For example, the network traffic enforcer 282 may check all packets (both from the network 290 and from the applications 274 ) to see if they match a channel opened by the application rule enforcer 284 .
  • the network traffic enforcer 282 may also drop other communications in a manner similar to a firewall. For example, the network traffic enforcer 282 may drop malformed packets and packets used for system scanning (e.g., ICMP (Internet Control Message Protocol) echo requests). Communications that are dropped by the network traffic enforcer are sent to the intrusion detector 280 .
  • ICMP Internet Control Message Protocol
  • the intrusion detector 280 examines the dropped communications to look for patterns signaling an intrusion prelude. For example, the intrusion detector 280 may look for system scans (e.g., ping), port scans (e.g., TCP-SYN (synchronization), TCP-FIN (finished), etc.), and OS fingerprinting. Frequently an intruder 294 will perform scanning operations on a system, or make some missteps, before an intrusion is launched. These operations may be detected by the intrusion detector 280 as an intrusion prelude.
  • system scans e.g., ping
  • port scans e.g., TCP-SYN (synchronization), TCP-FIN (finished), etc.
  • OS fingerprinting e.g., OS fingerprinting.
  • an intruder 294 will perform scanning operations on a system, or make some missteps, before an intrusion is launched. These operations may be detected by the intrusion detector 280 as an intrusion prelude.
  • the intrusion detector 280 may encourage these operations by generating fabricated responses to the dropped communications to catch the intruder 294 .
  • a fabricated response to blocked traffic may be used to gain knowledge about a potential intruder and their system for later use. For example, by selectively generating one or more fabricated responses to blocked inbound traffic, which would otherwise be blocked silently, significant information concerning a potential intruder's system and network may be obtained for use in later forensic analysis.
  • this collected information may be associated with the detected intrusion and may be especially useful, such as for use in prosecution of the intruder and/or other legal action (e.g., legal action requiring an intruder's Internet Service Provider (ISP) to take action, such as denying future network services to the intruder).
  • ISP Internet Service Provider
  • the intrusion detector 280 When an intrusion prelude is detected, the intrusion detector 280 then identifies and registers a source address for the intruder 294 and begins examining communications from that source to detect an intrusion. For example, the intrusion detector 280 may watch traffic from a potential intruder to look for packet level exploits such as launching intrusions using packet fragments (e.g., tear drop, Boink, etc.). Thus, the intrusion detector 280 may support packet reassembly to detect fragmentation related intrusions.
  • packet fragments e.g., tear drop, Boink, etc.
  • the intrusion detector 280 may block the traffic and/or report the intrusion to the central security server 292 . Additionally, the intrusion detector 280 may log the communications associated with a detected intrusion and intrusion prelude for forensic analysis.
  • an intrusion e.g., a packet exploit
  • FIG. 3 is a combined flowchart and state diagram illustrating a method of servicing network requests in an application rule enforcer (ARE) component of an integrated network intrusion detection system.
  • the method begins when an application and the ARE component are invoked ( 300 ).
  • the ARE component then identifies the invoked application ( 305 ).
  • the ARE component may determine the full path (directory and file name) of the loading application executable (e.g., “C:/Program Files/Application/application.exe”), examine machine instructions embodying the application (e.g., “application.exe”) to identify the application, and/or may crosscheck this identification with file properties information, such as name, size and version number. Examining the machine instructions may involve applying a hash function to the application's executable to generate a condensed representation (or hash value) of the executable. This hash value may then be compared with predefined hash values for known applications to identify the invoked application.
  • a hash function to the application's executable to generate a condensed representation (or hash value) of the executable. This hash value may then be compared with predefined hash values for known applications to identify the invoked application.
  • the hash function may be a message digest algorithm with a mathematical property that effectively guarantees that for any size message, a unique value of a fixed size (e.g., 128 bits) is returned.
  • the hash function may be part of a standardized message digest specification (e.g., Secure Hash Standard (SHA-1), defined in Federal Information Processing Standards Publication 180-1).
  • SHA-1 Secure Hash Standard
  • an application-specific network policy is loaded ( 310 ).
  • This network policy information may be loaded from a local repository and/or from a remote repository of network policy information (including dynamic loading from the remote repository to the local repository to keep the network policy information up to date as network policies change).
  • the ARE component enters an idle state 315 .
  • a network I/O request is made by the application, the request is compared with the application-specific network policy ( 320 ). If the policy is satisfied ( 325 ), a network traffic enforcer (NTE) component is notified to open a channel ( 330 ). For example, a message may be sent specifying a source IP address, a source port, a destination IP address, a destination port and a protocol for the opened channel.
  • NTE network traffic enforcer
  • an intrusion detector component is notified of the rejected request ( 335 ).
  • the notice may be that the application is behaving abnormally.
  • a single violation of network policy may be considered abnormal behavior for the application.
  • the application-specific network policy may be multi-tiered, such that certain violations are logged, but repeated and/or more severe violations of network policy constitute abnormal application behavior.
  • Such policies may include configurable thresholds for one or more characteristics of network communications.
  • the configurable thresholds may be set directly by the intrusion detector, and/or by a network administrator, after analysis of communication statistics for the application.
  • network administrators may set the configurable thresholds, such as by including them with intrusion signatures provided by security service providers, and/or the configurable thresholds may be auto-configurable, such as by monitoring communications during a defined time window.
  • the NTE component is notified of this closing channel ( 340 ).
  • FIG. 4 is a combined flowchart and state diagram illustrating a method of filtering network communications in a network traffic enforcer (NTE) component of an integrated network intrusion detection system.
  • the method begins in a monitoring state 400 , where communications are monitored to block unauthorized communications.
  • NTE network traffic enforcer
  • the opened channel is added to an authorization list ( 405 ), and monitoring continues.
  • FIG. 5A is a combined flowchart and state diagram illustrating a method of detecting intrusion preludes and intrusions in a first detector component of an integrated network intrusion detection system.
  • the method begins in an idle state 500 .
  • intrusion prelude patterns 505 .
  • Such patterns may include system scan, port scan and OS fingerprinting.
  • the source of the intrusion prelude is identified ( 530 ).
  • the identified source is a potential intruder, and thus communications from the potential intruder are monitored in an active monitoring state 535 .
  • This active monitoring may involve checking for packet level exploits, such as intrusions using packet fragments, as described above.
  • packet level exploits such as intrusions using packet fragments, as described above.
  • intrusion prelude patterns such as before ( 505 ).
  • additional sources may be added to a list of potential intruders to be monitored in the active monitoring state 535 .
  • a remedy is provided ( 540 ).
  • the intrusion activity may be logged, the traffic may be cut, countermeasures may be employed and/or an alert may be sent to a security operation center.
  • the monitored activity for the source is logged for later analysis, and the source-specific monitoring for that source is terminated ( 545 ). If this is the last source being monitored in the active monitoring state 535 , the method returns to the idle state 500 .
  • FIG. 5B is a combined flowchart and state diagram illustrating a method of detecting intrusions in a second detector component of an integrated network intrusion detection system.
  • the method begins in an idle state 550 .
  • the unauthorized request is compared with one or more configurable thresholds ( 555 ).
  • These configurable thresholds specify the type and/or number of requests that constitute abnormal application behavior.
  • the configurable thresholds may be set as described above.
  • a monitoring state 575 is entered, in which network communications for the application are monitored using the loaded parameters. If an intrusion is detected, a remedy is provided ( 580 ). For example, the intrusion activity may be logged, the traffic may be cut, countermeasures may be taken, and/or an alert may be sent to a security operation center. This remedy may be application-specific.
  • the method returns to the idle state 550 .
  • FIGS. 3 to 5 C show methods being performed in four separate components, these methods may also be combined into a single component or two or more components.
  • a first component being a combination of the NTE component and the first intrusion detector component
  • a second component being a combination of the ARE component and the second intrusion detector component, may perform a combination of the methods shown in FIGS. 3 and 5 B.
  • implementations of the systems and techniques described here may be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof.
  • ASICs application specific integrated circuits
  • These various implementations may include implementation in one or more computer programs that are executable/interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
  • FIG. 6 is a block diagram illustrating an example data processing system 600 .
  • the data processing system 600 includes a central processor 610 , which executes programs, performs data manipulations and controls tasks in the system 600 , thereby enabling the features and function described above.
  • the central processor 610 is coupled with one or more communication busses 615 .
  • the data processing system 600 includes a memory 620 , which may be volatile and/or non-volatile memory, and is coupled with the communications bus 615 .
  • the system 600 may also include one or more cache memories. These memory devices enable storage of instructions and data close to the central processor 610 for retrieval and execution.
  • the data processing system 600 may include a storage device 630 for accessing a medium 635 , which may be removable.
  • the medium 635 may be read-only or read/write media and may be magnetic-based, optical-based or magneto-optical-based media.
  • the data processing system 600 may also include one or more peripheral devices 640 ( 1 )- 640 ( n ) (collectively, devices 640 ), and one or more controllers and/or adapters for providing interface functions.
  • the devices 640 may be additional storage devices and media as described above, other storage interfaces and storage units, input devices and/or output devices.
  • the system 600 may further include a communication interface 650 , which allows software and data to be transferred, in the form of signals 654 over a channel 652 , between the system 600 and external devices, networks or information sources.
  • the signals 654 may embody instructions for causing the system 600 to perform operations.
  • the communication interface 650 may be a network interface designed for a particular type of network, protocol and channel medium, or may be designed to serve multiple networks, protocols and/or channel media.
  • the system 600 represents a programmable machine, and may include various devices such as embedded controllers and Programmable Logic Devices (PLDs).
  • Machine instructions also known as programs, software, software applications or code
  • PLDs Programmable Logic Devices
  • machine-readable medium refers to any medium or device used to provide machine instructions and/or data to the machine 600 .

Abstract

Intrusion preludes may be detected (including detection using fabricated responses to blocked network requests), and particular sources of network communications may be singled out for greater scrutiny, by performing intrusion analysis on packets blocked by a firewall. An integrated intrusion detection system uses an end-node firewall that is dynamically controlled using invoked-application information and a network policy. The system may use various alert levels to trigger heightened monitoring states, alerts sent to a security operation center, and/or logging of network activity for later forensic analysis. The system may monitor network traffic to block traffic that violates the network policy, monitor blocked traffic to detect an intrusion prelude, and monitor traffic from a potential intruder when an intrusion prelude is detected. The system also may track behavior of applications using the network policy to identify abnormal application behavior, and monitor traffic from an abnormally behaving application to identify an intrusion.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This application is a continuation application of and claims priority to U.S. patent application Ser. No. 10/066,140, filed Feb. 1, 2002. The disclosure of the prior application is considered part of (and is incorporated by reference in) the disclosure of this application.
  • BACKGROUND
  • The present application describes systems and techniques relating to network intrusion detection, for example, integrated network intrusion detection.
  • A machine network is a collection of nodes coupled together with wired and/or wireless communication links, such as coax cable, fiber optics and radio frequency bands. A machine network may be a single network or a collection of networks (e.g., an internetwork), and may use multiple networking protocols, including internetworking protocols (e.g., Internet Protocol (IP)). These protocols define the manner in which information is prepared for transmission through the network, and typically involve breaking data into segments generically known as packets (e.g., IP packets, ATM (Asynchronous Transfer Mode) cells) for transmission. A node may be any machine capable of communicating with other nodes over the communication links using one or more of the networking protocols.
  • These networking protocols are typically organized by a network architecture having multiple layers, where each layer provides communication services to the layer above it. A layered network architecture is commonly referred to as a protocol stack or network stack, where each layer of the stack has one or more protocols that provide specific services. The protocols may include shared-line protocols such as in Ethernet networks, connection-oriented switching protocols such as in ATM networks, and/or connectionless packet-switched protocols such as in IP.
  • As packets travel through a network, they are typically encapsulated within other packets multiple times. Encapsulation enables data to travel from a source process on one node to a destination process on another node, through multiple networks using different protocols and addressing schemes, without the two end nodes knowing anything about the intermediate addressing schemes and protocols.
  • Machine networks may provide powerful communication capabilities, but also may increase the difficulty of maintaining computer system security by making systems and data more accessible. Most networks are susceptible to attacks or improper use, both from inside and unauthorized access to data, destroy or bring down a computer system, prevent others from accessing a system and attempts to take control of a system. For example, some network intrusions exploit application anomalies to gain access to a system and infect it with a computer virus, such as Code Red or Nimba.
  • A common technique used to improve network security is to install a firewall, which restricts and controls the flow of traffic between networks, typically between an enterprise network and the Internet. Firewalls typically monitor incoming and outgoing traffic and filter, redirect, repackage and/or discard packets. A firewall may serve as a proxy and may enforce an organization's security policies.
  • Frequently, network administrators employ systems to detect network intrusions to improve network security. Traditional network intrusion detection (NID) systems attempt to examine every packet on a network in order to detect intrusions. These NID systems may be implemented as standalone systems (e.g., NFR (Network Flight Recorder), provided by Cisco Systems, Inc. of San Jose, Calif.), or they may be implemented as distributed node-based systems (e.g., BlackICE, provided by Network Ice Corporation of San Mateo California).
  • DRAWING DESCRIPTIONS
  • FIG. 1 is a combined flowchart and state diagram illustrating a method of monitoring network traffic to detect intrusions.
  • FIG. 2A is a block diagram illustrating a system implementing integrated network intrusion detection.
  • FIG. 2B is a block diagram illustrating another system implementing integrated network intrusion detection.
  • FIG. 3 is a combined flowchart and state diagram illustrating a method of servicing network requests in an application rule enforcer component of an integrated network intrusion detection system.
  • FIG. 4 is a combined flowchart and state diagram illustrating a method of filtering network communications in a network traffic enforcer component of an integrated network intrusion detection system.
  • FIG. 5A is a combined flowchart and state diagram illustrating a method of detecting intrusion preludes and intrusions in a first detector component of an integrated network intrusion detection system.
  • FIG. 5B is a combined flowchart and state diagram illustrating a method of detecting intrusions in a second detector component of an integrated network intrusion detection system.
  • FIG. 6 is a block diagram illustrating an example data processing system.
  • Details of one or more embodiments are set forth in the accompanying drawings and the description below. Other features and advantages may be apparent from the description and drawings, and from the claims.
  • DETAILED DESCRIPTION
  • The systems and techniques described here relate to integrated network intrusion detection. The description that follows frequently discusses intrusion detection in the context of IP networks, but the systems and techniques described apply equally to multiple types of machine communication networks and operating system environments.
  • As used herein, the term “application” means a software program, which is a collection of computing operations embodied by a set of instructions (e.g., one or more binary objects, one or more scripts, and/or one or more interpretable programs). The term “component” means a software program designed to operate with other components and/or applications. The term “process” means an executing software program. The term “execution context” means a set of processing cycles given to a process, such as a task in a multitasking operating system. Both an invoked application and an invoked component are a separate process, even if their functionality is interrelated and they share a single execution context. For example, an applet and a Web browser in which the applet runs are each a process. The term “applet” means a component designed specifically to be run from within an application. The term “thread” means a part of a software program that is given its own execution context.
  • The term “intrusion” means an attempt to break into and/or misuse a computing system. The term “intrusion prelude” means communication activities that typically precede an intrusion. The term “intrusion signature” means a communication pattern identified as corresponding to a known type of intrusion, including patterns that may be found in individual packets and patterns that may be gleaned from analyzing multiple packets.
  • The present inventor recognized the potential advantages of integrating firewall filtering information with network intrusion analysis. In typical network environments, most network traffic is legitimate and only a small portion of network communications may contain intrusions. By performing intrusion analysis on packets blocked by a firewall, intrusion preludes may be detected (including detection using fabricated responses to blocked network requests), and particular sources of network communications may be singled out for greater scrutiny. Thus, an overall amount of network traffic that needs to be monitored may be reduced, real-time intrusion detection may be improved, and more information about an intruder and the intruder's system and/or network may be obtained.
  • In addition, firewall functionality may be integrated with intrusion detection on end nodes (e.g., servers and hosts) in a network, such as an enterprise network, to further improve intrusion detection and network security. For example, a networked machine may include an intrusion detection system that functions in part as a dynamic firewall for the networked machine.
  • The intrusion detection system may include three components. The first component may be an application rule enforcer that authorizes network service requests from applications invoked on the networked machine and identifies abnormal behavior by an invoked application. The second component may be a network traffic enforcer that monitors inbound network communications and blocks those communications that fail to correspond to an authorized network service request. The third component may be an intrusion detector that monitors the blocked communications and identifies abnormal application behavior to determine when additional traffic monitoring is needed to detect an intrusion. Thus, the total number of communications (e.g., packets) that are examined may be reduced while intrusions may be detected more effectively.
  • FIG. 1 is a combined flowchart and state diagram illustrating a method of monitoring network traffic to detect intrusions. The method begins by identifying one or more applications invoked on a machine (100). This identification may be performed for an application by examining network communications generated by the application, system records for the application, and/or a set of instructions embodying the application.
  • Next a default state 105 is entered, in which inbound traffic (i.e., inbound network communications) and traffic corresponding to a watch list are monitored. These network communications are monitored to detect an intrusion prelude or an intrusion. Moreover, multiple levels of monitoring may be implemented in the default monitoring state 105.
  • When a new application is invoked, the new application is identified (100). When a request is received for network service (i.e., a network input/output (I/O) request) from an invoked application, a check is made as to whether the request violates a network policy (110). The network policy may include a system policy and/or an application-specific policy.
  • For example, the request may include information such as destination IP address, destination port, source port and type of request (e.g., bind, connect, accept, listen, send, receive, etc.). The network policy may include application-specific rules such as Application=Internet Explorer, destination port=Any, destination address=Any, source port=80, request=Listen, action=Allow. This rule states that the network policy allows any inbound traffic for the Internet Explorer application from any remote server through port 80. In addition to permissive rules that specify allowed communications, the network policy may also include restrictive rules that specify communications that are not allowed (e.g., a Deny action).
  • If the received request does not violate the network policy, the request is designated as authorized (115). Then, a communication channel for the request is enabled (120), and monitoring continues.
  • Rules similar to the policy rule above may be dynamically added to and removed from a network filter driver to open and close communication channels. Such filtering rules identify authorized network flows associated with invoked applications. In an IP network, a channel may be created by specifying an open channel for a network flow using five values: (1) source IP address, (2) source port, (3) destination IP address, (4) destination port, and (5) protocol. Additional and/or alternative values may be used to specify an open channel.
  • Following the creation of an open channel, inbound traffic that corresponds to the open channel is allowed, whereas inbound traffic that fails to correspond to an open channel is blocked in the monitoring state 105. Moreover, outbound traffic may also be monitored in the monitoring state 105, and disabled channels may also be created, such as by using the Deny action discussed above. Blocked traffic is monitored to detect an intrusion prelude, for example, a system scan, a port scan and/or an operating system (OS) fingerprinting. The blocked traffic may be checked for patterns that span multiple communications and/or multiple communication channels (e.g., multiple TCP/IP (Transmission Control Protocol/Internet Protocol) connections).
  • When an intrusion prelude is detected, a source of the intrusion prelude is identified (125). For example, a source IP addresses may be extracted from a packet that is part of the intrusion prelude. This source is then added to a watch list for increased monitoring (130), and monitoring continues. All packets from the identified source may then be monitored and these packets may be checked for intrusion signature(s). Additionally, multiple sources may be associated with each other, both in intrusion prelude detection and in subsequent intrusion detection, to counter distributed attacks.
  • If a received request violates the network policy, the request is designated as unauthorized (135). A determination is then made as to whether the application that generated the unauthorized request is behaving abnormally (140). This determination may be based on the number of unauthorized requests and/or on the severity of the unauthorized request generated by the application. For example, in one implementation, a single unauthorized request may be treated as abnormal behavior by an application. If the requesting application is behaving normally, monitoring continues.
  • When an application behaves abnormally, a level of monitoring for the application is increased (145), and monitoring continues. For example, the application may be added to a watch list to initiate monitoring of network communications both to and from the application. This monitoring may include searching packets for application-specific intrusion signatures.
  • FIG. 2A is a block diagram illustrating a system implementing integrated network intrusion detection. A networked machine 200 includes a network stack, which is a set of layered software modules implementing a defined protocol stack. The number and composition of layers in the network stack will vary with machine and network architecture, but generally includes a network driver 205, a network transport layer 210 (e.g., TCP/IP) and an application layer 220.
  • An intrusion detection system (IDS) 230 may be implemented between the network driver 205 and the network transport layer 210 so that all incoming packets may be monitored. Packet-level intrusion detection may be implemented in an NDIS (Network Driver Interface Specification) intermediate driver in a Windows environment. In addition, the IDS 230 may have additional components 232 placed elsewhere in the network stack. System-level intrusion detection may be implemented in one or more TDI (Transport Driver Interface) filter drivers, and application-level intrusion detection may be implemented in one or more components placed just below and/or just inside the application layer 220 (i.e., as part of a network interface library).
  • If an application-level component 234 is used as part of the IDS 230, network services requested by applications 224 go to the application-level component 234 first. As a result, the application-level component 234 knows which application requested which network service. In a Windows operating system environment, the application-level component 234 may be implemented as a WinSock (Windows Socket) Layer Service Provider (LSP) and/or as a TDI filter driver. WinSock is an Application Programming Interface (API) for developing Windows programs that communicate over a network using TCP/IP.
  • Alternatively, or in addition, application-level components 236 may be used for intrusion detection. Such components 236 load and run with each new network application 224 in an execution context 222 for that network application. These components 236 may perform authorization of network requests and application-specific intrusion signature detection such that the processing time consumed by these techniques affects only corresponding network applications.
  • The networked machine 200 is coupled with a network 240 that may provide communication links to a security operation center 242 and a potential intruder 244. The security operation center 242 may include a central security server. Various alert levels may be used in the IDS 230. These alert levels may trigger heightened monitoring states, cause alerts to be sent to the security operation center 242, and/or initiate logging of network activity, locally and/or with the central security server, for later forensic analysis.
  • The IDS 230 functions as a dynamic firewall for the networked machine 200. The IDS 230 monitors network traffic to block traffic that violates a network policy and monitors blocked traffic to detect an intrusion prelude. The IDS 230 monitors traffic from the potential intruder 244 when an intrusion prelude is detected. The IDS 230 may track behavior of applications 224 using a network policy that specifies behavior criteria (which may be application-specific) to identify abnormal application behavior. The IDS 230 may monitor traffic from an abnormally behaving application 224 a to identify an intrusion, including e.g. an intrusion connected with a Trojan Horse in the application.
  • FIG. 2B is a block diagram illustrating a system implementing integrated network intrusion detection. A networked machine 250 includes a network stack, as described above, and generally includes a network driver 255, a network transport layer 260 (e.g., TCP/IP) and an application layer 270. The networked machine 250 also includes an intrusion detection system divided into three components: an intrusion detector 280, a network traffic enforcer 282, and an application rule enforcer 284.
  • These components 280, 282, 284 may reside in fewer or greater than three software modules. For example, the intrusion detector 280 may include a kernel component that resides in a first module with the network traffic enforcer 282, and the intrusion detector 280 also may include a user component that resides in a second module with the application rule enforcer 284. Additionally, the application rule enforcer 284 may be a component that is invoked separately with each of multiple invoked applications 274, as described above.
  • The networked machine 250 is coupled with a network 290 that may provide communication links to a central security server 292 and a potential intruder 294.
  • As each application 274 requests network I/O service, the request is either authorized or rejected by the application rule enforcer 284. If the request is authorized, corresponding authorized communications 272 are allowed to pass from the application 274 to the network 290, and from the network 290 to the application 274. If a request is rejected, this rejected request is communicated to the intrusion detector 280.
  • If a request 276 is rejected, the intrusion detector 280 may determine that an application 274 a is behaving abnormally, and the intrusion detector 280 may then begin monitoring other communications 278 for the suspect application 274 a. This additional monitoring of communications 278 may involve checking for application-specific intrusion signatures, which may be dynamically loaded from the central security server 292.
  • The network traffic enforcer 282 monitors incoming network traffic. If an inbound communication 262 fails to correspond to an authorized request (i.e., the inbound communication was not effectively pre-approved by the application rule enforcer), the communication is dropped (i.e., blocked from passage to another layer in the network stack). Additionally, the network traffic enforcer 282 may monitor outbound communications in a similar manner. For example, the network traffic enforcer 282 may check all packets (both from the network 290 and from the applications 274) to see if they match a channel opened by the application rule enforcer 284.
  • Moreover, the network traffic enforcer 282 may also drop other communications in a manner similar to a firewall. For example, the network traffic enforcer 282 may drop malformed packets and packets used for system scanning (e.g., ICMP (Internet Control Message Protocol) echo requests). Communications that are dropped by the network traffic enforcer are sent to the intrusion detector 280.
  • The intrusion detector 280 examines the dropped communications to look for patterns signaling an intrusion prelude. For example, the intrusion detector 280 may look for system scans (e.g., ping), port scans (e.g., TCP-SYN (synchronization), TCP-FIN (finished), etc.), and OS fingerprinting. Frequently an intruder 294 will perform scanning operations on a system, or make some missteps, before an intrusion is launched. These operations may be detected by the intrusion detector 280 as an intrusion prelude.
  • Additionally, the intrusion detector 280 may encourage these operations by generating fabricated responses to the dropped communications to catch the intruder 294. A fabricated response to blocked traffic may be used to gain knowledge about a potential intruder and their system for later use. For example, by selectively generating one or more fabricated responses to blocked inbound traffic, which would otherwise be blocked silently, significant information concerning a potential intruder's system and network may be obtained for use in later forensic analysis. If the potential intruder later turns out to be an actual intruder, this collected information may be associated with the detected intrusion and may be especially useful, such as for use in prosecution of the intruder and/or other legal action (e.g., legal action requiring an intruder's Internet Service Provider (ISP) to take action, such as denying future network services to the intruder).
  • When an intrusion prelude is detected, the intrusion detector 280 then identifies and registers a source address for the intruder 294 and begins examining communications from that source to detect an intrusion. For example, the intrusion detector 280 may watch traffic from a potential intruder to look for packet level exploits such as launching intrusions using packet fragments (e.g., tear drop, Boink, etc.). Thus, the intrusion detector 280 may support packet reassembly to detect fragmentation related intrusions.
  • If the intrusion detector 280 detects an intrusion (e.g., a packet exploit), it may block the traffic and/or report the intrusion to the central security server 292. Additionally, the intrusion detector 280 may log the communications associated with a detected intrusion and intrusion prelude for forensic analysis.
  • FIG. 3 is a combined flowchart and state diagram illustrating a method of servicing network requests in an application rule enforcer (ARE) component of an integrated network intrusion detection system. The method begins when an application and the ARE component are invoked (300). The ARE component then identifies the invoked application (305).
  • To do so, the ARE component may determine the full path (directory and file name) of the loading application executable (e.g., “C:/Program Files/Application/application.exe”), examine machine instructions embodying the application (e.g., “application.exe”) to identify the application, and/or may crosscheck this identification with file properties information, such as name, size and version number. Examining the machine instructions may involve applying a hash function to the application's executable to generate a condensed representation (or hash value) of the executable. This hash value may then be compared with predefined hash values for known applications to identify the invoked application.
  • The hash function may be a message digest algorithm with a mathematical property that effectively guarantees that for any size message, a unique value of a fixed size (e.g., 128 bits) is returned. The hash function may be part of a standardized message digest specification (e.g., Secure Hash Standard (SHA-1), defined in Federal Information Processing Standards Publication 180-1).
  • Once the invoked application is identified, an application-specific network policy is loaded (310). This network policy information may be loaded from a local repository and/or from a remote repository of network policy information (including dynamic loading from the remote repository to the local repository to keep the network policy information up to date as network policies change). Then, the ARE component enters an idle state 315.
  • When a network I/O request is made by the application, the request is compared with the application-specific network policy (320). If the policy is satisfied (325), a network traffic enforcer (NTE) component is notified to open a channel (330). For example, a message may be sent specifying a source IP address, a source port, a destination IP address, a destination port and a protocol for the opened channel.
  • If the policy is not satisfied, an intrusion detector component is notified of the rejected request (335). Alternatively, the notice may be that the application is behaving abnormally. For example, a single violation of network policy may be considered abnormal behavior for the application. Alternatively, the application-specific network policy may be multi-tiered, such that certain violations are logged, but repeated and/or more severe violations of network policy constitute abnormal application behavior.
  • Such policies may include configurable thresholds for one or more characteristics of network communications. The configurable thresholds may be set directly by the intrusion detector, and/or by a network administrator, after analysis of communication statistics for the application. Thus, network administrators may set the configurable thresholds, such as by including them with intrusion signatures provided by security service providers, and/or the configurable thresholds may be auto-configurable, such as by monitoring communications during a defined time window.
  • When an open channel is closed, the NTE component is notified of this closing channel (340).
  • FIG. 4 is a combined flowchart and state diagram illustrating a method of filtering network communications in a network traffic enforcer (NTE) component of an integrated network intrusion detection system. The method begins in a monitoring state 400, where communications are monitored to block unauthorized communications. When a notification of an opened channel is received, the opened channel is added to an authorization list (405), and monitoring continues.
  • When an unauthorized communication is received, a copy of the communication is sent to an intrusion detector component (410). Then the unauthorized communication is blocked (i.e., dropped) (415), and monitoring continues. When a notification of a closed channel is received, the closed channel is removed from the authorization list (420), and monitoring continues. Thus, network communications that have not been pre-approved by the ARE component are blocked and copied to the intrusion detector.
  • FIG. 5A is a combined flowchart and state diagram illustrating a method of detecting intrusion preludes and intrusions in a first detector component of an integrated network intrusion detection system. The method begins in an idle state 500. When a blocked communication is received, it is checked for intrusion prelude patterns (505). Such patterns may include system scan, port scan and OS fingerprinting.
  • A check is made to determine if an intrusion prelude is present (510). If not, a check is made to determine if a response is needed to encourage an intruder (515). If so, a fabricated response is generated and sent to the potential intruder (520). Then, or if a fabricated response was not needed, the present communication activity is logged for future use in detecting intrusion preludes (525).
  • If an intrusion prelude is detected, the source of the intrusion prelude is identified (530). The identified source is a potential intruder, and thus communications from the potential intruder are monitored in an active monitoring state 535. This active monitoring may involve checking for packet level exploits, such as intrusions using packet fragments, as described above. When a blocked communication is received, it is checked for intrusion prelude patterns, as before (505). Thus, additional sources may be added to a list of potential intruders to be monitored in the active monitoring state 535.
  • If an intrusion is detected, a remedy is provided (540). For example, the intrusion activity may be logged, the traffic may be cut, countermeasures may be employed and/or an alert may be sent to a security operation center.
  • If a pre-defined time elapses for an identified source, the monitored activity for the source is logged for later analysis, and the source-specific monitoring for that source is terminated (545). If this is the last source being monitored in the active monitoring state 535, the method returns to the idle state 500.
  • FIG. 5B is a combined flowchart and state diagram illustrating a method of detecting intrusions in a second detector component of an integrated network intrusion detection system. The method begins in an idle state 550. When an unauthorized request occurs, the unauthorized request is compared with one or more configurable thresholds (555). These configurable thresholds specify the type and/or number of requests that constitute abnormal application behavior. The configurable thresholds may be set as described above.
  • A check is then made for abnormal behavior (560). If the application is not behaving abnormally, the unauthorized request is logged for later use (565). If the application is behaving abnormally, monitoring parameters for the application are loaded (570). These parameters may include application-specific intrusion detection signatures.
  • Then, a monitoring state 575 is entered, in which network communications for the application are monitored using the loaded parameters. If an intrusion is detected, a remedy is provided (580). For example, the intrusion activity may be logged, the traffic may be cut, countermeasures may be taken, and/or an alert may be sent to a security operation center. This remedy may be application-specific.
  • If a predefined time elapses, in which no intrusion is detected, the monitored communications for the application are logged for later analysis (585). Then, the method returns to the idle state 550.
  • Although FIGS. 3 to 5C show methods being performed in four separate components, these methods may also be combined into a single component or two or more components. For example, a first component, being a combination of the NTE component and the first intrusion detector component, may perform a combination of the methods shown in FIGS. 4 and 5A. A second component, being a combination of the ARE component and the second intrusion detector component, may perform a combination of the methods shown in FIGS. 3 and 5B.
  • Various implementations of the systems and techniques described here may be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations may include implementation in one or more computer programs that are executable/interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
  • FIG. 6 is a block diagram illustrating an example data processing system 600. The data processing system 600 includes a central processor 610, which executes programs, performs data manipulations and controls tasks in the system 600, thereby enabling the features and function described above. The central processor 610 is coupled with one or more communication busses 615.
  • The data processing system 600 includes a memory 620, which may be volatile and/or non-volatile memory, and is coupled with the communications bus 615. The system 600 may also include one or more cache memories. These memory devices enable storage of instructions and data close to the central processor 610 for retrieval and execution.
  • The data processing system 600 may include a storage device 630 for accessing a medium 635, which may be removable. The medium 635 may be read-only or read/write media and may be magnetic-based, optical-based or magneto-optical-based media. The data processing system 600 may also include one or more peripheral devices 640(1)-640(n) (collectively, devices 640), and one or more controllers and/or adapters for providing interface functions. The devices 640 may be additional storage devices and media as described above, other storage interfaces and storage units, input devices and/or output devices.
  • The system 600 may further include a communication interface 650, which allows software and data to be transferred, in the form of signals 654 over a channel 652, between the system 600 and external devices, networks or information sources. The signals 654 may embody instructions for causing the system 600 to perform operations. The communication interface 650 may be a network interface designed for a particular type of network, protocol and channel medium, or may be designed to serve multiple networks, protocols and/or channel media.
  • The system 600 represents a programmable machine, and may include various devices such as embedded controllers and Programmable Logic Devices (PLDs). Machine instructions (also known as programs, software, software applications or code) may be stored in the machine 600 or delivered to the machine 600 over a communication interface. These instructions, when executed, enable the machine 600 to perform the features and function described above.
  • As used herein, the term “machine-readable medium” refers to any medium or device used to provide machine instructions and/or data to the machine 600. The various implementations described above have been presented by way of example only, and not limitation. Thus, other embodiments may be within the scope of the following claims.

Claims (22)

1. (canceled)
2. A machine-implemented method comprising:
receiving requests for network communication services from an invoked application;
selectively designating each of the received requests as authorized or unauthorized based on a network policy; and monitoring network communications, for the invoked application, based on the designating of the requests.
3. The method of claim 2, wherein selectively designating each of the received requests comprises selectively designating each of the received requests as authorized or unauthorized based on an application-specific network policy corresponding to the invoked application.
4. The method of claim 3, wherein monitoring the network communications comprises monitoring outbound network communications.
5. The method of claim 2, further comprising increasing a monitoring level for the invoked application when the invoked application behaves abnormally.
6. The method of claim 5, wherein increasing the monitoring level for the invoked application comprises adding the invoked application to a watch list to initiate monitoring of network communications both to and from the application, including searching packets for application-specific intrusion signatures.
7. The method of claim 2, wherein monitoring of the network communications for the invoked application comprises monitoring in an intrusion detection system component invoked with the invoked application.
8. The method of claim 7, wherein the intrusion detection system component and the invoked application run within a single execution context.
9. A machine-readable medium embodying machine instructions for causing one or more machines to perform operations comprising:
receiving requests for network communication services from an invoked application;
selectively designating each of the received requests as authorized or unauthorized based on a network policy; and
monitoring network communications, for the invoked application, based on the designating of the requests.
10. The machine-readable medium of claim 9, wherein selectively designating each of the received requests comprises selectively designating each of the received requests as authorized or unauthorized based on an application-specific network policy corresponding to the invoked application.
11. The machine-readable medium of claim 10, wherein monitoring the network communications comprises monitoring outbound network communications.
12. The machine-readable medium of claim 9, the operations further comprising increasing a monitoring level for the invoked application when the invoked application behaves abnormally.
13. The machine-readable medium of claim 12, wherein increasing the monitoring level for the invoked application comprises adding the invoked application to a watch list to initiate monitoring of network communications both to and from the application, including searching packets for application-specific intrusion signatures.
14. The machine-readable medium of claim 9, wherein monitoring of the network communications for the invoked application comprises monitoring in an intrusion detection system component invoked with the invoked application.
15. The machine-readable medium of claim 14, wherein the intrusion detection system component and the invoked application run within a single execution context.
16. A system comprising:
a processor;
a communication interface coupled with the processor; and
a machine-readable medium operatively coupled with the processor and embodying machine instructions for causing the processor to perform operations comprising:
receiving requests for network communication services from an invoked application;
selectively designating each of the received requests as authorized or unauthorized based on a network policy; and
monitoring network communications, for the invoked application, based on the designating of the requests.
17. The system of claim 16, wherein selectively designating each of the received requests comprises selectively designating each of the received requests as authorized or unauthorized based on an application-specific network policy corresponding to the invoked application.
18. The system of claim 17, wherein monitoring the network communications comprises monitoring outbound network communications.
19. The system of claim 16, the operations further comprising increasing a monitoring level for the invoked application when the invoked application behaves abnormally.
20. The system of claim 19, wherein increasing the monitoring level for the invoked application comprises adding the invoked application to a watch list to initiate monitoring of network communications both to and from the application, including searching packets for application-specific intrusion signatures.
21. The system of claim 16, wherein monitoring of the network communications for the invoked application comprises monitoring in an intrusion detection system component invoked with the invoked application.
22. The system of claim 21, wherein the intrusion detection system component and the invoked application run within a single execution context.
US11/702,908 2002-02-01 2007-02-05 Integrated network intrusion detection Abandoned US20070209070A1 (en)

Priority Applications (5)

Application Number Priority Date Filing Date Title
US11/702,908 US20070209070A1 (en) 2002-02-01 2007-02-05 Integrated network intrusion detection
US12/649,018 US8752173B2 (en) 2002-02-01 2009-12-29 Integrated network intrusion detection
US14/300,420 US9143525B2 (en) 2002-02-01 2014-06-10 Integrated network intrusion detection
US14/861,232 US10044738B2 (en) 2002-02-01 2015-09-22 Integrated network intrusion detection
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Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070147239A1 (en) * 2005-12-28 2007-06-28 Chun-Te Wu Terminal and Related Computer-Implemented Method for Detecting Malicious Data for Computer Network
US20080313738A1 (en) * 2007-06-15 2008-12-18 Broadcom Corporation Multi-Stage Deep Packet Inspection for Lightweight Devices
US20100122317A1 (en) * 2002-02-01 2010-05-13 Satyendra Yadav Integrated Network Intrusion Detection
US20150128246A1 (en) * 2013-11-07 2015-05-07 Attivo Networks Inc. Methods and apparatus for redirecting attacks on a network
US20160173452A1 (en) * 2013-06-27 2016-06-16 Jeong Hoan Seo Multi-connection system and method for service using internet protocol
US20190140958A1 (en) * 2017-11-07 2019-05-09 Facebook, Inc. Hierarchical orchestration of a computer network
US11579857B2 (en) 2020-12-16 2023-02-14 Sentinel Labs Israel Ltd. Systems, methods and devices for device fingerprinting and automatic deployment of software in a computing network using a peer-to-peer approach
US11580218B2 (en) 2019-05-20 2023-02-14 Sentinel Labs Israel Ltd. Systems and methods for executable code detection, automatic feature extraction and position independent code detection
US11616812B2 (en) 2016-12-19 2023-03-28 Attivo Networks Inc. Deceiving attackers accessing active directory data
US11625485B2 (en) 2014-08-11 2023-04-11 Sentinel Labs Israel Ltd. Method of malware detection and system thereof
US11695800B2 (en) 2016-12-19 2023-07-04 SentinelOne, Inc. Deceiving attackers accessing network data
US11716341B2 (en) 2017-08-08 2023-08-01 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US11888897B2 (en) 2018-02-09 2024-01-30 SentinelOne, Inc. Implementing decoys in a network environment
US11886591B2 (en) 2014-08-11 2024-01-30 Sentinel Labs Israel Ltd. Method of remediating operations performed by a program and system thereof
US11899782B1 (en) 2021-07-13 2024-02-13 SentinelOne, Inc. Preserving DLL hooks

Families Citing this family (300)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040073617A1 (en) 2000-06-19 2004-04-15 Milliken Walter Clark Hash-based systems and methods for detecting and preventing transmission of unwanted e-mail
US20030149887A1 (en) * 2002-02-01 2003-08-07 Satyendra Yadav Application-specific network intrusion detection
US8209756B1 (en) 2002-02-08 2012-06-26 Juniper Networks, Inc. Compound attack detection in a computer network
US7734752B2 (en) * 2002-02-08 2010-06-08 Juniper Networks, Inc. Intelligent integrated network security device for high-availability applications
US8370936B2 (en) 2002-02-08 2013-02-05 Juniper Networks, Inc. Multi-method gateway-based network security systems and methods
US7650634B2 (en) 2002-02-08 2010-01-19 Juniper Networks, Inc. Intelligent integrated network security device
US8578480B2 (en) 2002-03-08 2013-11-05 Mcafee, Inc. Systems and methods for identifying potentially malicious messages
US7870203B2 (en) 2002-03-08 2011-01-11 Mcafee, Inc. Methods and systems for exposing messaging reputation to an end user
US7903549B2 (en) 2002-03-08 2011-03-08 Secure Computing Corporation Content-based policy compliance systems and methods
US7694128B2 (en) 2002-03-08 2010-04-06 Mcafee, Inc. Systems and methods for secure communication delivery
US7124438B2 (en) 2002-03-08 2006-10-17 Ciphertrust, Inc. Systems and methods for anomaly detection in patterns of monitored communications
US8561167B2 (en) 2002-03-08 2013-10-15 Mcafee, Inc. Web reputation scoring
US7096498B2 (en) 2002-03-08 2006-08-22 Cipher Trust, Inc. Systems and methods for message threat management
US7693947B2 (en) 2002-03-08 2010-04-06 Mcafee, Inc. Systems and methods for graphically displaying messaging traffic
US6941467B2 (en) * 2002-03-08 2005-09-06 Ciphertrust, Inc. Systems and methods for adaptive message interrogation through multiple queues
US8132250B2 (en) 2002-03-08 2012-03-06 Mcafee, Inc. Message profiling systems and methods
US20060015942A1 (en) 2002-03-08 2006-01-19 Ciphertrust, Inc. Systems and methods for classification of messaging entities
DE60332448D1 (en) * 2002-04-17 2010-06-17 Computer Ass Think Inc NERKODE IN A COMPANY NETWORK
US8910241B2 (en) * 2002-04-25 2014-12-09 Citrix Systems, Inc. Computer security system
US20030204596A1 (en) * 2002-04-29 2003-10-30 Satyendra Yadav Application-based network quality of service provisioning
US7359962B2 (en) * 2002-04-30 2008-04-15 3Com Corporation Network security system integration
US7086089B2 (en) * 2002-05-20 2006-08-01 Airdefense, Inc. Systems and methods for network security
US7277404B2 (en) * 2002-05-20 2007-10-02 Airdefense, Inc. System and method for sensing wireless LAN activity
US7383577B2 (en) * 2002-05-20 2008-06-03 Airdefense, Inc. Method and system for encrypted network management and intrusion detection
US7532895B2 (en) * 2002-05-20 2009-05-12 Air Defense, Inc. Systems and methods for adaptive location tracking
US7058796B2 (en) * 2002-05-20 2006-06-06 Airdefense, Inc. Method and system for actively defending a wireless LAN against attacks
US7042852B2 (en) * 2002-05-20 2006-05-09 Airdefense, Inc. System and method for wireless LAN dynamic channel change with honeypot trap
EP1512075A1 (en) * 2002-05-22 2005-03-09 Lucid Security Corporation Adaptive intrusion detection system
US20030232598A1 (en) * 2002-06-13 2003-12-18 Daniel Aljadeff Method and apparatus for intrusion management in a wireless network using physical location determination
ATE341144T1 (en) * 2002-07-12 2006-10-15 Cit Alcatel FIREWALL FOR DYNAMIC ACCESS GRANTING AND DENIAL TO NETWORK RESOURCES
US8140660B1 (en) * 2002-07-19 2012-03-20 Fortinet, Inc. Content pattern recognition language processor and methods of using the same
US7114183B1 (en) * 2002-08-28 2006-09-26 Mcafee, Inc. Network adaptive baseline monitoring system and method
US7509679B2 (en) * 2002-08-30 2009-03-24 Symantec Corporation Method, system and computer program product for security in a global computer network transaction
US7748039B2 (en) * 2002-08-30 2010-06-29 Symantec Corporation Method and apparatus for detecting malicious code in an information handling system
US7331062B2 (en) * 2002-08-30 2008-02-12 Symantec Corporation Method, computer software, and system for providing end to end security protection of an online transaction
US7454499B2 (en) * 2002-11-07 2008-11-18 Tippingpoint Technologies, Inc. Active network defense system and method
US8312535B1 (en) 2002-12-12 2012-11-13 Mcafee, Inc. System, method, and computer program product for interfacing a plurality of related applications
US8122498B1 (en) 2002-12-12 2012-02-21 Mcafee, Inc. Combined multiple-application alert system and method
US8239941B1 (en) 2002-12-13 2012-08-07 Mcafee, Inc. Push alert system, method, and computer program product
US8990723B1 (en) 2002-12-13 2015-03-24 Mcafee, Inc. System, method, and computer program product for managing a plurality of applications via a single interface
US7418730B2 (en) * 2002-12-17 2008-08-26 International Business Machines Corporation Automatic client responses to worm or hacker attacks
US20040205183A1 (en) * 2003-03-10 2004-10-14 Sandvine Incorporated Method and system for avoiding tracking communication connection state until accepted
US7603710B2 (en) * 2003-04-03 2009-10-13 Network Security Technologies, Inc. Method and system for detecting characteristics of a wireless network
US7355996B2 (en) * 2004-02-06 2008-04-08 Airdefense, Inc. Systems and methods for adaptive monitoring with bandwidth constraints
US7885190B1 (en) 2003-05-12 2011-02-08 Sourcefire, Inc. Systems and methods for determining characteristics of a network based on flow analysis
US8065725B2 (en) * 2003-05-30 2011-11-22 Yuliang Zheng Systems and methods for enhanced network security
US7596807B2 (en) * 2003-07-03 2009-09-29 Arbor Networks, Inc. Method and system for reducing scope of self-propagating attack code in network
BR0318459A (en) * 2003-08-11 2006-09-12 Telecom Italia Spa intrusion detection system and method for detecting unauthorized use of a communication network
US20050050213A1 (en) * 2003-09-03 2005-03-03 James Clough Authorizing network requests
US7725936B2 (en) * 2003-10-31 2010-05-25 International Business Machines Corporation Host-based network intrusion detection systems
US7581249B2 (en) * 2003-11-14 2009-08-25 Enterasys Networks, Inc. Distributed intrusion response system
US8839417B1 (en) * 2003-11-17 2014-09-16 Mcafee, Inc. Device, system and method for defending a computer network
KR100522138B1 (en) 2003-12-31 2005-10-18 주식회사 잉카인터넷 Flexible network security system and method to permit trustful process
WO2005071923A1 (en) * 2004-01-20 2005-08-04 Intrusic, Inc Systems and methods for monitoring data transmissions to detect a compromised network
KR100609170B1 (en) * 2004-02-13 2006-08-02 엘지엔시스(주) system of network security and working method thereof
US7895448B1 (en) * 2004-02-18 2011-02-22 Symantec Corporation Risk profiling
US20050187934A1 (en) * 2004-02-24 2005-08-25 Covelight Systems, Inc. Methods, systems and computer program products for geography and time monitoring of a server application user
US20050188080A1 (en) * 2004-02-24 2005-08-25 Covelight Systems, Inc. Methods, systems and computer program products for monitoring user access for a server application
US20050188222A1 (en) * 2004-02-24 2005-08-25 Covelight Systems, Inc. Methods, systems and computer program products for monitoring user login activity for a server application
US7373524B2 (en) * 2004-02-24 2008-05-13 Covelight Systems, Inc. Methods, systems and computer program products for monitoring user behavior for a server application
US7496500B2 (en) * 2004-03-01 2009-02-24 Microsoft Corporation Systems and methods that determine intent of data and respond to the data based on the intent
FR2868230B1 (en) * 2004-03-25 2012-06-08 Netasq DEVICE AND METHOD FOR DETECTING AND PREVENTING INTRUSION IN A COMPUTER NETWORK
US7904960B2 (en) * 2004-04-27 2011-03-08 Cisco Technology, Inc. Source/destination operating system type-based IDS virtualization
RU2006143768A (en) * 2004-05-12 2008-06-20 Алькатель (Fr) AROMATIC RESTRICTION OF THE NETWORK VIOLENT
US8074277B2 (en) * 2004-06-07 2011-12-06 Check Point Software Technologies, Inc. System and methodology for intrusion detection and prevention
US7539681B2 (en) * 2004-07-26 2009-05-26 Sourcefire, Inc. Methods and systems for multi-pattern searching
US8108929B2 (en) * 2004-10-19 2012-01-31 Reflex Systems, LLC Method and system for detecting intrusive anomalous use of a software system using multiple detection algorithms
US8196199B2 (en) * 2004-10-19 2012-06-05 Airdefense, Inc. Personal wireless monitoring agent
US8635690B2 (en) 2004-11-05 2014-01-21 Mcafee, Inc. Reputation based message processing
KR100639969B1 (en) * 2004-12-02 2006-11-01 한국전자통신연구원 Apparatus for abnormal traffic control and method thereof
US7990967B2 (en) 2005-01-06 2011-08-02 Rockwell Automation Technologies, Inc. Firewall method and apparatus for industrial systems
US7610610B2 (en) * 2005-01-10 2009-10-27 Mcafee, Inc. Integrated firewall, IPS, and virus scanner system and method
US7310669B2 (en) 2005-01-19 2007-12-18 Lockdown Networks, Inc. Network appliance for vulnerability assessment auditing over multiple networks
US8520512B2 (en) 2005-01-26 2013-08-27 Mcafee, Inc. Network appliance for customizable quarantining of a node on a network
US20060164199A1 (en) * 2005-01-26 2006-07-27 Lockdown Networks, Inc. Network appliance for securely quarantining a node on a network
US7810138B2 (en) 2005-01-26 2010-10-05 Mcafee, Inc. Enabling dynamic authentication with different protocols on the same port for a switch
US7810151B1 (en) 2005-01-27 2010-10-05 Juniper Networks, Inc. Automated change detection within a network environment
US7809826B1 (en) 2005-01-27 2010-10-05 Juniper Networks, Inc. Remote aggregation of network traffic profiling data
US7937755B1 (en) 2005-01-27 2011-05-03 Juniper Networks, Inc. Identification of network policy violations
US7769851B1 (en) 2005-01-27 2010-08-03 Juniper Networks, Inc. Application-layer monitoring and profiling network traffic
US7797411B1 (en) * 2005-02-02 2010-09-14 Juniper Networks, Inc. Detection and prevention of encapsulated network attacks using an intermediate device
US20060259950A1 (en) * 2005-02-18 2006-11-16 Ulf Mattsson Multi-layer system for privacy enforcement and monitoring of suspicious data access behavior
US7937480B2 (en) 2005-06-02 2011-05-03 Mcafee, Inc. Aggregation of reputation data
JP4742144B2 (en) * 2005-06-06 2011-08-10 インターナショナル・ビジネス・マシーンズ・コーポレーション Method and computer program for identifying a device attempting to penetrate a TCP / IP protocol based network
US7746862B1 (en) 2005-08-02 2010-06-29 Juniper Networks, Inc. Packet processing in a multiple processor system
US7891000B1 (en) * 2005-08-05 2011-02-15 Cisco Technology, Inc. Methods and apparatus for monitoring and reporting network activity of applications on a group of host computers
US9015090B2 (en) 2005-09-06 2015-04-21 Daniel Chien Evaluating a questionable network communication
US9912677B2 (en) 2005-09-06 2018-03-06 Daniel Chien Evaluating a questionable network communication
US8621604B2 (en) * 2005-09-06 2013-12-31 Daniel Chien Evaluating a questionable network communication
US9674145B2 (en) 2005-09-06 2017-06-06 Daniel Chien Evaluating a questionable network communication
US7814548B2 (en) 2005-09-13 2010-10-12 Honeywell International Inc. Instance based learning framework for effective behavior profiling and anomaly intrusion detection
US7733803B2 (en) * 2005-11-14 2010-06-08 Sourcefire, Inc. Systems and methods for modifying network map attributes
US8046833B2 (en) * 2005-11-14 2011-10-25 Sourcefire, Inc. Intrusion event correlation with network discovery information
US8082586B2 (en) * 2005-11-22 2011-12-20 International Business Machines Corporation Snoop echo response extractor
US8763113B2 (en) * 2005-11-28 2014-06-24 Threatmetrix Pty Ltd Method and system for processing a stream of information from a computer network using node based reputation characteristics
US7921165B2 (en) * 2005-11-30 2011-04-05 Microsoft Corporation Retaining mail for availability after relay
US8495743B2 (en) * 2005-12-16 2013-07-23 Cisco Technology, Inc. Methods and apparatus providing automatic signature generation and enforcement
US7734754B2 (en) * 2005-12-28 2010-06-08 Microsoft Corporation Reviewing effectiveness of communication rules system
US7810160B2 (en) * 2005-12-28 2010-10-05 Microsoft Corporation Combining communication policies into common rules store
US7715800B2 (en) 2006-01-13 2010-05-11 Airdefense, Inc. Systems and methods for wireless intrusion detection using spectral analysis
WO2007106902A2 (en) * 2006-03-15 2007-09-20 Daniel Chien Identifying unauthorized access to a network resource
US7971251B2 (en) 2006-03-17 2011-06-28 Airdefense, Inc. Systems and methods for wireless security using distributed collaboration of wireless clients
KR100748246B1 (en) * 2006-03-29 2007-08-10 한국전자통신연구원 Multi-step integrated security monitoring system and method using intrusion detection system log collection engine and traffic statistic generation engine
US8028026B2 (en) * 2006-05-31 2011-09-27 Microsoft Corporation Perimeter message filtering with extracted user-specific preferences
US8549295B2 (en) 2006-05-31 2013-10-01 Microsoft Corporation Establishing secure, mutually authenticated communication credentials
US8726020B2 (en) * 2006-05-31 2014-05-13 Microsoft Corporation Updating configuration information to a perimeter network
US7970013B2 (en) 2006-06-16 2011-06-28 Airdefense, Inc. Systems and methods for wireless network content filtering
US20080010538A1 (en) * 2006-06-27 2008-01-10 Symantec Corporation Detecting suspicious embedded malicious content in benign file formats
US7948988B2 (en) * 2006-07-27 2011-05-24 Sourcefire, Inc. Device, system and method for analysis of fragments in a fragment train
US8166113B2 (en) * 2006-08-02 2012-04-24 Microsoft Corporation Access limited EMM distribution lists
US8281392B2 (en) 2006-08-11 2012-10-02 Airdefense, Inc. Methods and systems for wired equivalent privacy and Wi-Fi protected access protection
CA2672908A1 (en) * 2006-10-06 2008-04-17 Sourcefire, Inc. Device, system and method for use of micro-policies in intrusion detection/prevention
US7779156B2 (en) 2007-01-24 2010-08-17 Mcafee, Inc. Reputation based load balancing
US7949716B2 (en) 2007-01-24 2011-05-24 Mcafee, Inc. Correlation and analysis of entity attributes
US8214497B2 (en) 2007-01-24 2012-07-03 Mcafee, Inc. Multi-dimensional reputation scoring
US8763114B2 (en) 2007-01-24 2014-06-24 Mcafee, Inc. Detecting image spam
US8179798B2 (en) 2007-01-24 2012-05-15 Mcafee, Inc. Reputation based connection throttling
CA2714549A1 (en) * 2007-02-09 2008-08-14 Smobile Systems, Inc. Off-line mms malware scanning system and method
US8069352B2 (en) * 2007-02-28 2011-11-29 Sourcefire, Inc. Device, system and method for timestamp analysis of segments in a transmission control protocol (TCP) session
US8955105B2 (en) * 2007-03-14 2015-02-10 Microsoft Corporation Endpoint enabled for enterprise security assessment sharing
US8413247B2 (en) * 2007-03-14 2013-04-02 Microsoft Corporation Adaptive data collection for root-cause analysis and intrusion detection
US8959568B2 (en) * 2007-03-14 2015-02-17 Microsoft Corporation Enterprise security assessment sharing
US20080229419A1 (en) * 2007-03-16 2008-09-18 Microsoft Corporation Automated identification of firewall malware scanner deficiencies
US7882542B2 (en) * 2007-04-02 2011-02-01 Microsoft Corporation Detecting compromised computers by correlating reputation data with web access logs
US8127353B2 (en) * 2007-04-30 2012-02-28 Sourcefire, Inc. Real-time user awareness for a computer network
US20080307526A1 (en) * 2007-06-07 2008-12-11 Mi5 Networks Method to perform botnet detection
KR20090011481A (en) 2007-07-26 2009-02-02 삼성전자주식회사 Method for intrusion detecting in a terminal device and apparatus therefor
US8291495B1 (en) * 2007-08-08 2012-10-16 Juniper Networks, Inc. Identifying applications for intrusion detection systems
US8214895B2 (en) * 2007-09-26 2012-07-03 Microsoft Corporation Whitelist and blacklist identification data
US8286243B2 (en) * 2007-10-23 2012-10-09 International Business Machines Corporation Blocking intrusion attacks at an offending host
US20090113039A1 (en) * 2007-10-25 2009-04-30 At&T Knowledge Ventures, L.P. Method and system for content handling
US8185930B2 (en) 2007-11-06 2012-05-22 Mcafee, Inc. Adjusting filter or classification control settings
US8112800B1 (en) 2007-11-08 2012-02-07 Juniper Networks, Inc. Multi-layered application classification and decoding
US8045458B2 (en) 2007-11-08 2011-10-25 Mcafee, Inc. Prioritizing network traffic
US8160975B2 (en) 2008-01-25 2012-04-17 Mcafee, Inc. Granular support vector machine with random granularity
US9264441B2 (en) * 2008-03-24 2016-02-16 Hewlett Packard Enterprise Development Lp System and method for securing a network from zero-day vulnerability exploits
US8589503B2 (en) 2008-04-04 2013-11-19 Mcafee, Inc. Prioritizing network traffic
US8474043B2 (en) * 2008-04-17 2013-06-25 Sourcefire, Inc. Speed and memory optimization of intrusion detection system (IDS) and intrusion prevention system (IPS) rule processing
US8621608B2 (en) * 2008-04-29 2013-12-31 Mcafee, Inc. System, method, and computer program product for dynamically adjusting a level of security applied to a system
US9779234B2 (en) * 2008-06-18 2017-10-03 Symantec Corporation Software reputation establishment and monitoring system and method
US8856926B2 (en) * 2008-06-27 2014-10-07 Juniper Networks, Inc. Dynamic policy provisioning within network security devices
US20090328210A1 (en) * 2008-06-30 2009-12-31 Microsoft Corporation Chain of events tracking with data tainting for automated security feedback
US7903566B2 (en) * 2008-08-20 2011-03-08 The Boeing Company Methods and systems for anomaly detection using internet protocol (IP) traffic conversation data
US8813220B2 (en) * 2008-08-20 2014-08-19 The Boeing Company Methods and systems for internet protocol (IP) packet header collection and storage
US8726382B2 (en) * 2008-08-20 2014-05-13 The Boeing Company Methods and systems for automated detection and tracking of network attacks
US7995496B2 (en) * 2008-08-20 2011-08-09 The Boeing Company Methods and systems for internet protocol (IP) traffic conversation detection and storage
US8762515B2 (en) * 2008-08-20 2014-06-24 The Boeing Company Methods and systems for collection, tracking, and display of near real time multicast data
US8272055B2 (en) 2008-10-08 2012-09-18 Sourcefire, Inc. Target-based SMB and DCE/RPC processing for an intrusion detection system or intrusion prevention system
US8572717B2 (en) 2008-10-09 2013-10-29 Juniper Networks, Inc. Dynamic access control policy with port restrictions for a network security appliance
US7607174B1 (en) * 2008-12-31 2009-10-20 Kaspersky Lab Zao Adaptive security for portable information devices
US7584508B1 (en) 2008-12-31 2009-09-01 Kaspersky Lab Zao Adaptive security for information devices
US9398043B1 (en) * 2009-03-24 2016-07-19 Juniper Networks, Inc. Applying fine-grain policy action to encapsulated network attacks
CN101854340B (en) * 2009-04-03 2015-04-01 瞻博网络公司 Behavior based communication analysis carried out based on access control information
US8694624B2 (en) * 2009-05-19 2014-04-08 Symbol Technologies, Inc. Systems and methods for concurrent wireless local area network access and sensing
WO2011130510A1 (en) 2010-04-16 2011-10-20 Sourcefire, Inc. System and method for near-real time network attack detection, and system and method for unified detection via detection routing
US9098333B1 (en) 2010-05-07 2015-08-04 Ziften Technologies, Inc. Monitoring computer process resource usage
US8621638B2 (en) 2010-05-14 2013-12-31 Mcafee, Inc. Systems and methods for classification of messaging entities
US9552478B2 (en) 2010-05-18 2017-01-24 AO Kaspersky Lab Team security for portable information devices
US8433790B2 (en) 2010-06-11 2013-04-30 Sourcefire, Inc. System and method for assigning network blocks to sensors
US8671182B2 (en) 2010-06-22 2014-03-11 Sourcefire, Inc. System and method for resolving operating system or service identity conflicts
KR101188307B1 (en) 2010-12-24 2012-10-09 (주) 세인트 시큐리티 System and method of network activity monitoring to particular process
US8499348B1 (en) * 2010-12-28 2013-07-30 Amazon Technologies, Inc. Detection of and responses to network attacks
US8601034B2 (en) 2011-03-11 2013-12-03 Sourcefire, Inc. System and method for real time data awareness
US9467360B2 (en) * 2011-06-27 2016-10-11 Sk Telecom Co., Ltd. System, device and method for managing network traffic by using monitoring and filtering policies
US8955128B1 (en) 2011-07-27 2015-02-10 Francesco Trama Systems and methods for selectively regulating network traffic
US8707434B2 (en) 2011-08-17 2014-04-22 Mcafee, Inc. System and method for indirect interface monitoring and plumb-lining
US8881258B2 (en) * 2011-08-24 2014-11-04 Mcafee, Inc. System, method, and computer program for preventing infections from spreading in a network environment using dynamic application of a firewall policy
US10620241B2 (en) 2012-02-17 2020-04-14 Perspecta Labs Inc. Method and system for packet acquisition, analysis and intrusion detection in field area networks
WO2013123434A1 (en) 2012-02-17 2013-08-22 Tt Government Solutions, Inc. Multi-function electric meter adapter and method for use
US9027125B2 (en) * 2012-05-01 2015-05-05 Taasera, Inc. Systems and methods for network flow remediation based on risk correlation
CN103959711B (en) * 2012-09-07 2018-02-23 Sk电信有限公司 Utilize monitoring strategies and the system and method for filtering policy managing network flow
CN103810424B (en) * 2012-11-05 2017-02-08 腾讯科技(深圳)有限公司 Method and device for identifying abnormal application programs
GB2508174B (en) * 2012-11-22 2015-04-08 F Secure Corp Detecting application behavior
US9304955B2 (en) * 2012-12-18 2016-04-05 Advanced Micro Devices, Inc. Techniques for identifying and handling processor interrupts
EP2948882A4 (en) 2013-01-24 2016-08-10 Vencore Labs Inc Method and system for visualizing and analyzing a field area network
US9245147B1 (en) * 2013-01-30 2016-01-26 White Badger Group, LLC State machine reference monitor for information system security
US8910285B2 (en) 2013-04-19 2014-12-09 Lastline, Inc. Methods and systems for reciprocal generation of watch-lists and malware signatures
WO2014193708A1 (en) * 2013-05-25 2014-12-04 North Carolina State University Large-scale, time-sensitive secure distributed control systems and methods
US10084791B2 (en) 2013-08-14 2018-09-25 Daniel Chien Evaluating a questionable network communication
US9246935B2 (en) 2013-10-14 2016-01-26 Intuit Inc. Method and system for dynamic and comprehensive vulnerability management
US9313281B1 (en) 2013-11-13 2016-04-12 Intuit Inc. Method and system for creating and dynamically deploying resource specific discovery agents for determining the state of a cloud computing environment
US9501345B1 (en) 2013-12-23 2016-11-22 Intuit Inc. Method and system for creating enriched log data
US9323926B2 (en) 2013-12-30 2016-04-26 Intuit Inc. Method and system for intrusion and extrusion detection
US20150215327A1 (en) * 2014-01-28 2015-07-30 Intuit Inc. Method and system for extrusion and intrusion detection in a cloud computing environment using network communications devices
US9325726B2 (en) 2014-02-03 2016-04-26 Intuit Inc. Method and system for virtual asset assisted extrusion and intrusion detection in a cloud computing environment
US20150304343A1 (en) 2014-04-18 2015-10-22 Intuit Inc. Method and system for providing self-monitoring, self-reporting, and self-repairing virtual assets in a cloud computing environment
US9866581B2 (en) 2014-06-30 2018-01-09 Intuit Inc. Method and system for secure delivery of information to computing environments
US10757133B2 (en) 2014-02-21 2020-08-25 Intuit Inc. Method and system for creating and deploying virtual assets
US9276945B2 (en) 2014-04-07 2016-03-01 Intuit Inc. Method and system for providing security aware applications
US9245117B2 (en) 2014-03-31 2016-01-26 Intuit Inc. Method and system for comparing different versions of a cloud based application in a production environment using segregated backend systems
US11294700B2 (en) 2014-04-18 2022-04-05 Intuit Inc. Method and system for enabling self-monitoring virtual assets to correlate external events with characteristic patterns associated with the virtual assets
US9374389B2 (en) 2014-04-25 2016-06-21 Intuit Inc. Method and system for ensuring an application conforms with security and regulatory controls prior to deployment
US10122753B2 (en) 2014-04-28 2018-11-06 Sophos Limited Using reputation to avoid false malware detections
US9392015B2 (en) * 2014-04-28 2016-07-12 Sophos Limited Advanced persistent threat detection
US9917851B2 (en) 2014-04-28 2018-03-13 Sophos Limited Intrusion detection using a heartbeat
US9900322B2 (en) 2014-04-30 2018-02-20 Intuit Inc. Method and system for providing permissions management
US9319415B2 (en) 2014-04-30 2016-04-19 Intuit Inc. Method and system for providing reference architecture pattern-based permissions management
US9330263B2 (en) 2014-05-27 2016-05-03 Intuit Inc. Method and apparatus for automating the building of threat models for the public cloud
US10102082B2 (en) 2014-07-31 2018-10-16 Intuit Inc. Method and system for providing automated self-healing virtual assets
US9473481B2 (en) 2014-07-31 2016-10-18 Intuit Inc. Method and system for providing a virtual asset perimeter
US10951637B2 (en) 2014-08-28 2021-03-16 Suse Llc Distributed detection of malicious cloud actors
US9935829B1 (en) 2014-09-24 2018-04-03 Amazon Technologies, Inc. Scalable packet processing service
US9323556B2 (en) 2014-09-30 2016-04-26 Amazon Technologies, Inc. Programmatic event detection and message generation for requests to execute program code
US10048974B1 (en) 2014-09-30 2018-08-14 Amazon Technologies, Inc. Message-based computation request scheduling
US9146764B1 (en) 2014-09-30 2015-09-29 Amazon Technologies, Inc. Processing event messages for user requests to execute program code
US9600312B2 (en) 2014-09-30 2017-03-21 Amazon Technologies, Inc. Threading as a service
US9678773B1 (en) 2014-09-30 2017-06-13 Amazon Technologies, Inc. Low latency computational capacity provisioning
US9715402B2 (en) 2014-09-30 2017-07-25 Amazon Technologies, Inc. Dynamic code deployment and versioning
US9830193B1 (en) 2014-09-30 2017-11-28 Amazon Technologies, Inc. Automatic management of low latency computational capacity
US9948661B2 (en) 2014-10-29 2018-04-17 At&T Intellectual Property I, L.P. Method and apparatus for detecting port scans in a network
US11165812B2 (en) 2014-12-03 2021-11-02 Splunk Inc. Containment of security threats within a computing environment
US9537788B2 (en) 2014-12-05 2017-01-03 Amazon Technologies, Inc. Automatic determination of resource sizing
WO2016097757A1 (en) 2014-12-18 2016-06-23 Sophos Limited A method and system for network access control based on traffic monitoring and vulnerability detection using process related information
US9733967B2 (en) 2015-02-04 2017-08-15 Amazon Technologies, Inc. Security protocols for low latency execution of program code
US9588790B1 (en) 2015-02-04 2017-03-07 Amazon Technologies, Inc. Stateful virtual compute system
US9667656B2 (en) 2015-03-30 2017-05-30 Amazon Technologies, Inc. Networking flow logs for multi-tenant environments
US9930103B2 (en) 2015-04-08 2018-03-27 Amazon Technologies, Inc. Endpoint management system providing an application programming interface proxy service
US9785476B2 (en) 2015-04-08 2017-10-10 Amazon Technologies, Inc. Endpoint management system and virtual compute system
US10536357B2 (en) 2015-06-05 2020-01-14 Cisco Technology, Inc. Late data detection in data center
US10142353B2 (en) * 2015-06-05 2018-11-27 Cisco Technology, Inc. System for monitoring and managing datacenters
US20170012923A1 (en) 2015-07-08 2017-01-12 International Business Machines Corporation Preventing a user from missing unread documents
US10148694B1 (en) * 2015-10-01 2018-12-04 Symantec Corporation Preventing data loss over network channels by dynamically monitoring file system operations of a process
US10754701B1 (en) 2015-12-16 2020-08-25 Amazon Technologies, Inc. Executing user-defined code in response to determining that resources expected to be utilized comply with resource restrictions
US9811434B1 (en) 2015-12-16 2017-11-07 Amazon Technologies, Inc. Predictive management of on-demand code execution
US9910713B2 (en) 2015-12-21 2018-03-06 Amazon Technologies, Inc. Code execution request routing
US10067801B1 (en) 2015-12-21 2018-09-04 Amazon Technologies, Inc. Acquisition and maintenance of compute capacity
US10075416B2 (en) 2015-12-30 2018-09-11 Juniper Networks, Inc. Network session data sharing
US10014937B1 (en) 2016-03-11 2018-07-03 Juniper Networks, Inc. Timing synchronization and intrusion detection via an optical supervisory channel (OSC)
US10243971B2 (en) * 2016-03-25 2019-03-26 Arbor Networks, Inc. System and method for retrospective network traffic analysis
US11132213B1 (en) 2016-03-30 2021-09-28 Amazon Technologies, Inc. Dependency-based process of pre-existing data sets at an on demand code execution environment
US10891145B2 (en) 2016-03-30 2021-01-12 Amazon Technologies, Inc. Processing pre-existing data sets at an on demand code execution environment
US9948681B1 (en) 2016-03-31 2018-04-17 Amazon Technologies, Inc. Access control monitoring through policy management
US10567388B1 (en) 2016-03-31 2020-02-18 Amazon Technologies, Inc. Automatic account resource and policy decommissioning
US10542044B2 (en) 2016-04-29 2020-01-21 Attivo Networks Inc. Authentication incident detection and management
US10102040B2 (en) 2016-06-29 2018-10-16 Amazon Technologies, Inc Adjusting variable limit on concurrent code executions
US10225234B2 (en) * 2016-08-31 2019-03-05 Fortress Cyber Security, LLC Systems and methods for geoprocessing-based computing network security
US11089064B1 (en) * 2016-09-12 2021-08-10 Skyhigh Networks, Llc Cloud security policy enforcement for custom web applications
US10798111B2 (en) * 2016-09-14 2020-10-06 International Business Machines Corporation Detecting intrusion attempts in data transmission sessions
US10884787B1 (en) 2016-09-23 2021-01-05 Amazon Technologies, Inc. Execution guarantees in an on-demand network code execution system
US11119813B1 (en) 2016-09-30 2021-09-14 Amazon Technologies, Inc. Mapreduce implementation using an on-demand network code execution system
US10528725B2 (en) 2016-11-04 2020-01-07 Microsoft Technology Licensing, Llc IoT security service
US10972456B2 (en) 2016-11-04 2021-04-06 Microsoft Technology Licensing, Llc IoT device authentication
US10542006B2 (en) 2016-11-22 2020-01-21 Daniel Chien Network security based on redirection of questionable network access
US10382436B2 (en) 2016-11-22 2019-08-13 Daniel Chien Network security based on device identifiers and network addresses
US10491625B2 (en) 2017-10-03 2019-11-26 International Business Machines Corporation Retrieving network packets corresponding to detected abnormal application activity
TWI672605B (en) * 2017-11-29 2019-09-21 財團法人資訊工業策進會 System and method for identifying application layer behavior
US10564946B1 (en) 2017-12-13 2020-02-18 Amazon Technologies, Inc. Dependency handling in an on-demand network code execution system
US10542025B2 (en) 2017-12-26 2020-01-21 International Business Machines Corporation Automatic traffic classification of web applications and services based on dynamic analysis
US10831898B1 (en) 2018-02-05 2020-11-10 Amazon Technologies, Inc. Detecting privilege escalations in code including cross-service calls
US10733085B1 (en) 2018-02-05 2020-08-04 Amazon Technologies, Inc. Detecting impedance mismatches due to cross-service calls
US10353678B1 (en) * 2018-02-05 2019-07-16 Amazon Technologies, Inc. Detecting code characteristic alterations due to cross-service calls
US10725752B1 (en) 2018-02-13 2020-07-28 Amazon Technologies, Inc. Dependency handling in an on-demand network code execution system
US10776091B1 (en) 2018-02-26 2020-09-15 Amazon Technologies, Inc. Logging endpoint in an on-demand code execution system
CN110213198A (en) * 2018-02-28 2019-09-06 中标软件有限公司 The monitoring method and system of network flow
US11140020B1 (en) 2018-03-01 2021-10-05 Amazon Technologies, Inc. Availability-enhancing gateways for network traffic in virtualized computing environments
US10862912B2 (en) * 2018-03-23 2020-12-08 Juniper Networks, Inc. Tracking host threats in a network and enforcing threat policy actions for the host threats
US10853115B2 (en) 2018-06-25 2020-12-01 Amazon Technologies, Inc. Execution of auxiliary functions in an on-demand network code execution system
US10649749B1 (en) 2018-06-26 2020-05-12 Amazon Technologies, Inc. Cross-environment application of tracing information for improved code execution
US11146569B1 (en) 2018-06-28 2021-10-12 Amazon Technologies, Inc. Escalation-resistant secure network services using request-scoped authentication information
US10949237B2 (en) 2018-06-29 2021-03-16 Amazon Technologies, Inc. Operating system customization in an on-demand network code execution system
US11099870B1 (en) 2018-07-25 2021-08-24 Amazon Technologies, Inc. Reducing execution times in an on-demand network code execution system using saved machine states
US11243953B2 (en) 2018-09-27 2022-02-08 Amazon Technologies, Inc. Mapreduce implementation in an on-demand network code execution system and stream data processing system
US11099917B2 (en) 2018-09-27 2021-08-24 Amazon Technologies, Inc. Efficient state maintenance for execution environments in an on-demand code execution system
US11188622B2 (en) 2018-09-28 2021-11-30 Daniel Chien Systems and methods for computer security
US10884812B2 (en) 2018-12-13 2021-01-05 Amazon Technologies, Inc. Performance-based hardware emulation in an on-demand network code execution system
US10826912B2 (en) 2018-12-14 2020-11-03 Daniel Chien Timestamp-based authentication
US10848489B2 (en) 2018-12-14 2020-11-24 Daniel Chien Timestamp-based authentication with redirection
US11010188B1 (en) 2019-02-05 2021-05-18 Amazon Technologies, Inc. Simulated data object storage using on-demand computation of data objects
US11861386B1 (en) 2019-03-22 2024-01-02 Amazon Technologies, Inc. Application gateways in an on-demand network code execution system
US11119809B1 (en) 2019-06-20 2021-09-14 Amazon Technologies, Inc. Virtualization-based transaction handling in an on-demand network code execution system
US11115404B2 (en) 2019-06-28 2021-09-07 Amazon Technologies, Inc. Facilitating service connections in serverless code executions
US11190609B2 (en) 2019-06-28 2021-11-30 Amazon Technologies, Inc. Connection pooling for scalable network services
US11159528B2 (en) 2019-06-28 2021-10-26 Amazon Technologies, Inc. Authentication to network-services using hosted authentication information
US11055112B2 (en) 2019-09-27 2021-07-06 Amazon Technologies, Inc. Inserting executions of owner-specified code into input/output path of object storage service
US11656892B1 (en) 2019-09-27 2023-05-23 Amazon Technologies, Inc. Sequential execution of user-submitted code and native functions
US11106477B2 (en) 2019-09-27 2021-08-31 Amazon Technologies, Inc. Execution of owner-specified code during input/output path to object storage service
US11386230B2 (en) 2019-09-27 2022-07-12 Amazon Technologies, Inc. On-demand code obfuscation of data in input path of object storage service
US11394761B1 (en) 2019-09-27 2022-07-19 Amazon Technologies, Inc. Execution of user-submitted code on a stream of data
US11360948B2 (en) 2019-09-27 2022-06-14 Amazon Technologies, Inc. Inserting owner-specified data processing pipelines into input/output path of object storage service
US11023416B2 (en) 2019-09-27 2021-06-01 Amazon Technologies, Inc. Data access control system for object storage service based on owner-defined code
US11263220B2 (en) 2019-09-27 2022-03-01 Amazon Technologies, Inc. On-demand execution of object transformation code in output path of object storage service
US10908927B1 (en) 2019-09-27 2021-02-02 Amazon Technologies, Inc. On-demand execution of object filter code in output path of object storage service
US10996961B2 (en) 2019-09-27 2021-05-04 Amazon Technologies, Inc. On-demand indexing of data in input path of object storage service
US11550944B2 (en) 2019-09-27 2023-01-10 Amazon Technologies, Inc. Code execution environment customization system for object storage service
US11023311B2 (en) 2019-09-27 2021-06-01 Amazon Technologies, Inc. On-demand code execution in input path of data uploaded to storage service in multiple data portions
US11250007B1 (en) 2019-09-27 2022-02-15 Amazon Technologies, Inc. On-demand execution of object combination code in output path of object storage service
US11416628B2 (en) 2019-09-27 2022-08-16 Amazon Technologies, Inc. User-specific data manipulation system for object storage service based on user-submitted code
US11119826B2 (en) 2019-11-27 2021-09-14 Amazon Technologies, Inc. Serverless call distribution to implement spillover while avoiding cold starts
US10942795B1 (en) 2019-11-27 2021-03-09 Amazon Technologies, Inc. Serverless call distribution to utilize reserved capacity without inhibiting scaling
US11677754B2 (en) 2019-12-09 2023-06-13 Daniel Chien Access control systems and methods
US11714682B1 (en) 2020-03-03 2023-08-01 Amazon Technologies, Inc. Reclaiming computing resources in an on-demand code execution system
US11188391B1 (en) 2020-03-11 2021-11-30 Amazon Technologies, Inc. Allocating resources to on-demand code executions under scarcity conditions
US11775640B1 (en) 2020-03-30 2023-10-03 Amazon Technologies, Inc. Resource utilization-based malicious task detection in an on-demand code execution system
US11438145B2 (en) 2020-05-31 2022-09-06 Daniel Chien Shared key generation based on dual clocks
US11509463B2 (en) 2020-05-31 2022-11-22 Daniel Chien Timestamp-based shared key generation
US11550713B1 (en) 2020-11-25 2023-01-10 Amazon Technologies, Inc. Garbage collection in distributed systems using life cycled storage roots
US11593270B1 (en) 2020-11-25 2023-02-28 Amazon Technologies, Inc. Fast distributed caching using erasure coded object parts
US11388210B1 (en) 2021-06-30 2022-07-12 Amazon Technologies, Inc. Streaming analytics using a serverless compute system
US20220014551A1 (en) * 2021-09-24 2022-01-13 Intel Corporation Method and apparatus to reduce risk of denial of service resource acquisition attacks in a data center
EP4235470A1 (en) 2022-03-25 2023-08-30 ZOE Life Technologies AG Method and network component for protecting networked infrastructures

Citations (76)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5008936A (en) * 1988-12-09 1991-04-16 The Exchange System Limited Partnership Backup/restore technique in a microcomputer-based encryption system
US5421006A (en) * 1992-05-07 1995-05-30 Compaq Computer Corp. Method and apparatus for assessing integrity of computer system software
US5787409A (en) * 1996-05-17 1998-07-28 International Business Machines Corporation Dynamic monitoring architecture
US5802275A (en) * 1994-06-22 1998-09-01 Lucent Technologies Inc. Isolation of non-secure software from secure software to limit virus infection
US5919257A (en) * 1997-08-08 1999-07-06 Novell, Inc. Networked workstation intrusion detection system
US5948104A (en) * 1997-05-23 1999-09-07 Neuromedical Systems, Inc. System and method for automated anti-viral file update
US5960798A (en) * 1998-02-26 1999-10-05 Fashion Nails, Inc. Method and apparatus for creating art on an object such as a person's fingernail or toenail
US5970143A (en) * 1995-11-22 1999-10-19 Walker Asset Management Lp Remote-auditing of computer generated outcomes, authenticated billing and access control, and software metering system using cryptographic and other protocols
US5978936A (en) * 1997-11-19 1999-11-02 International Business Machines Corporation Run time error probe in a network computing environment
US5983348A (en) * 1997-09-10 1999-11-09 Trend Micro Incorporated Computer network malicious code scanner
US5987611A (en) * 1996-12-31 1999-11-16 Zone Labs, Inc. System and methodology for managing internet access on a per application basis for client computers connected to the internet
US6065118A (en) * 1996-08-09 2000-05-16 Citrix Systems, Inc. Mobile code isolation cage
US6219706B1 (en) * 1998-10-16 2001-04-17 Cisco Technology, Inc. Access control for networks
US6266811B1 (en) * 1997-12-31 2001-07-24 Network Associates Method and system for custom computer software installation using rule-based installation engine and simplified script computer program
US6279113B1 (en) * 1998-03-16 2001-08-21 Internet Tools, Inc. Dynamic signature inspection-based network intrusion detection
US6282546B1 (en) * 1998-06-30 2001-08-28 Cisco Technology, Inc. System and method for real-time insertion of data into a multi-dimensional database for network intrusion detection and vulnerability assessment
US6301668B1 (en) * 1998-12-29 2001-10-09 Cisco Technology, Inc. Method and system for adaptive network security using network vulnerability assessment
US20010052012A1 (en) * 2000-06-30 2001-12-13 Rinne Janne Petri Quality of service definition for data streams
US20020010771A1 (en) * 2000-05-24 2002-01-24 Davide Mandato Universal QoS adaptation framework for mobile multimedia applications
US6370584B1 (en) * 1998-01-13 2002-04-09 Trustees Of Boston University Distributed routing
US6411941B1 (en) * 1998-05-21 2002-06-25 Beeble, Inc. Method of restricting software operation within a license limitation
US20020103720A1 (en) * 2001-01-29 2002-08-01 Cline Linda S. Extensible network services system
US20020120853A1 (en) * 2001-02-27 2002-08-29 Networks Associates Technology, Inc. Scripted distributed denial-of-service (DDoS) attack discrimination using turing tests
US20020129278A1 (en) * 1998-10-15 2002-09-12 Doron Elgressy Method and system for the prevention of undesirable activities of executable objects
US20020143911A1 (en) * 2001-03-30 2002-10-03 John Vicente Host-based network traffic control system
US20020143914A1 (en) * 2001-03-29 2002-10-03 Cihula Joseph F. Network-aware policy deployment
US6463470B1 (en) * 1998-10-26 2002-10-08 Cisco Technology, Inc. Method and apparatus of storing policies for policy-based management of quality of service treatments of network data traffic flows
US6466984B1 (en) * 1999-07-02 2002-10-15 Cisco Technology, Inc. Method and apparatus for policy-based management of quality of service treatments of network data traffic flows by integrating policies with application programs
US6484203B1 (en) * 1998-11-09 2002-11-19 Sri International, Inc. Hierarchical event monitoring and analysis
US6496483B1 (en) * 1999-08-18 2002-12-17 At&T Corp. Secure detection of an intercepted targeted IP phone from multiple monitoring locations
US20020194317A1 (en) * 2001-04-26 2002-12-19 Yasusi Kanada Method and system for controlling a policy-based network
US6501752B1 (en) * 1999-08-18 2002-12-31 At&T Corp. Flexible packet technique for monitoring calls spanning different backbone networks
US6553377B1 (en) * 2000-03-31 2003-04-22 Network Associates, Inc. System and process for maintaining a plurality of remote security applications using a modular framework in a distributed computing environment
US20030084323A1 (en) * 2001-10-31 2003-05-01 Gales George S. Network intrusion detection system and method
US6574663B1 (en) * 1999-08-31 2003-06-03 Intel Corporation Active topology discovery in active networks
US20030126468A1 (en) * 2001-05-25 2003-07-03 Markham Thomas R. Distributed firewall system and method
US20030149888A1 (en) * 2002-02-01 2003-08-07 Satyendra Yadav Integrated network intrusion detection
US20030149887A1 (en) * 2002-02-01 2003-08-07 Satyendra Yadav Application-specific network intrusion detection
US20030159070A1 (en) * 2001-05-28 2003-08-21 Yaron Mayer System and method for comprehensive general generic protection for computers against malicious programs that may steal information and/or cause damages
US20030200439A1 (en) * 2002-04-17 2003-10-23 Moskowitz Scott A. Methods, systems and devices for packet watermarking and efficient provisioning of bandwidth
US6640248B1 (en) * 1998-07-10 2003-10-28 Malibu Networks, Inc. Application-aware, quality of service (QoS) sensitive, media access control (MAC) layer
US20030204596A1 (en) * 2002-04-29 2003-10-30 Satyendra Yadav Application-based network quality of service provisioning
US6665799B1 (en) * 1999-04-28 2003-12-16 Dvi Acquisition Corp. Method and computer software code for providing security for a computer software program
US6681331B1 (en) * 1999-05-11 2004-01-20 Cylant, Inc. Dynamic software system intrusion detection
US6694436B1 (en) * 1998-05-22 2004-02-17 Activcard Terminal and system for performing secure electronic transactions
US6701463B1 (en) * 2000-09-05 2004-03-02 Motorola, Inc. Host specific monitor script for networked computer clusters
US20040078467A1 (en) * 2000-11-02 2004-04-22 George Grosner Switching system
US6735702B1 (en) * 1999-08-31 2004-05-11 Intel Corporation Method and system for diagnosing network intrusion
US6742015B1 (en) * 1999-08-31 2004-05-25 Accenture Llp Base services patterns in a netcentric environment
US6751659B1 (en) * 2000-03-31 2004-06-15 Intel Corporation Distributing policy information in a communication network
US6807583B2 (en) * 1997-09-24 2004-10-19 Carleton University Method of determining causal connections between events recorded during process execution
US6807156B1 (en) * 2000-11-07 2004-10-19 Telefonaktiebolaget Lm Ericsson (Publ) Scalable real-time quality of service monitoring and analysis of service dependent subscriber satisfaction in IP networks
US6816903B1 (en) * 1997-05-27 2004-11-09 Novell, Inc. Directory enabled policy management tool for intelligent traffic management
US6816973B1 (en) * 1998-12-29 2004-11-09 Cisco Technology, Inc. Method and system for adaptive network security using intelligent packet analysis
US6826716B2 (en) * 2001-09-26 2004-11-30 International Business Machines Corporation Test programs for enterprise web applications
US6832260B2 (en) * 2001-07-26 2004-12-14 International Business Machines Corporation Methods, systems and computer program products for kernel based transaction processing
US6842861B1 (en) * 2000-03-24 2005-01-11 Networks Associates Technology, Inc. Method and system for detecting viruses on handheld computers
US6851057B1 (en) * 1999-11-30 2005-02-01 Symantec Corporation Data driven detection of viruses
US6868062B1 (en) * 2000-03-28 2005-03-15 Intel Corporation Managing data traffic on multiple ports
US6871224B1 (en) * 1999-01-04 2005-03-22 Cisco Technology, Inc. Facility to transmit network management data to an umbrella management system
US6879587B1 (en) * 2000-06-30 2005-04-12 Intel Corporation Packet processing in a router architecture
US6892303B2 (en) * 2000-01-06 2005-05-10 International Business Machines Corporation Method and system for caching virus-free file certificates
US20050193218A1 (en) * 1999-01-22 2005-09-01 Joshua Susser Techniques for permitting access across a context barrier on a small footprint device using an entry point object
US6952776B1 (en) * 1999-09-22 2005-10-04 International Business Machines Corporation Method and apparatus for increasing virus detection speed using a database
US6957348B1 (en) * 2000-01-10 2005-10-18 Ncircle Network Security, Inc. Interoperability of vulnerability and intrusion detection systems
US6971015B1 (en) * 2000-03-29 2005-11-29 Microsoft Corporation Methods and arrangements for limiting access to computer controlled functions and devices
US6973577B1 (en) * 2000-05-26 2005-12-06 Mcafee, Inc. System and method for dynamically detecting computer viruses through associative behavioral analysis of runtime state
US6996845B1 (en) * 2000-11-28 2006-02-07 S.P.I. Dynamics Incorporated Internet security analysis system and process
US6996843B1 (en) * 1999-08-30 2006-02-07 Symantec Corporation System and method for detecting computer intrusions
US7065790B1 (en) * 2001-12-21 2006-06-20 Mcafee, Inc. Method and system for providing computer malware names from multiple anti-virus scanners
US7069330B1 (en) * 2001-07-05 2006-06-27 Mcafee, Inc. Control of interaction between client computer applications and network resources
US7089294B1 (en) * 2000-08-24 2006-08-08 International Business Machines Corporation Methods, systems and computer program products for server based type of service classification of a communication request
US7103666B2 (en) * 2001-01-12 2006-09-05 Siemens Medical Solutions Health Services Corporation System and user interface supporting concurrent application operation and interoperability
US7171688B2 (en) * 2001-06-25 2007-01-30 Intel Corporation System, method and computer program for the detection and restriction of the network activity of denial of service attack software
US7181768B1 (en) * 1999-10-28 2007-02-20 Cigital Computer intrusion detection system and method based on application monitoring
US7225430B2 (en) * 2001-07-26 2007-05-29 Landesk Software Limited Software code management method and apparatus

Family Cites Families (38)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5398196A (en) * 1993-07-29 1995-03-14 Chambers; David A. Method and apparatus for detection of computer viruses
US5864683A (en) * 1994-10-12 1999-01-26 Secure Computing Corporartion System for providing secure internetwork by connecting type enforcing secure computers to external network for limiting access to data based on user and process access rights
US5623601A (en) * 1994-11-18 1997-04-22 Milkway Networks Corporation Apparatus and method for providing a secure gateway for communication and data exchanges between networks
US6226749B1 (en) 1995-07-31 2001-05-01 Hewlett-Packard Company Method and apparatus for operating resources under control of a security module or other secure processor
US6072857A (en) * 1996-12-19 2000-06-06 Bellsouth Intellectual Property Management Corporation Methods and system for monitoring the operational status of a network component in an advanced intelligent network
US5968176A (en) * 1997-05-29 1999-10-19 3Com Corporation Multilayer firewall system
US6104700A (en) * 1997-08-29 2000-08-15 Extreme Networks Policy based quality of service
US6400707B1 (en) * 1998-08-27 2002-06-04 Bell Atlantic Network Services, Inc. Real time firewall security
US6158010A (en) * 1998-10-28 2000-12-05 Crosslogix, Inc. System and method for maintaining security in a distributed computer network
AU2164700A (en) 1998-12-09 2000-06-26 Network Ice Corporation A method and apparatus for providing network and computer system security
US6725377B1 (en) * 1999-03-12 2004-04-20 Networks Associates Technology, Inc. Method and system for updating anti-intrusion software
US6981155B1 (en) 1999-07-14 2005-12-27 Symantec Corporation System and method for computer security
US7089591B1 (en) * 1999-07-30 2006-08-08 Symantec Corporation Generic detection and elimination of marco viruses
US6226811B1 (en) * 1999-11-05 2001-05-08 Edwin W. Fagan Epidermal scrubbing device
US6990591B1 (en) 1999-11-18 2006-01-24 Secureworks, Inc. Method and system for remotely configuring and monitoring a communication device
US7822629B2 (en) * 1999-12-15 2010-10-26 Hewlett-Packard Development Company, L.P. Customer profiling apparatus for conducting customer behavior pattern analysis, and method for comparing customer behavior patterns
AUPQ621600A0 (en) * 2000-03-14 2000-04-06 Overs, Ronald Ernest Grand piano action
US7159237B2 (en) * 2000-03-16 2007-01-02 Counterpane Internet Security, Inc. Method and system for dynamic network intrusion monitoring, detection and response
US7574740B1 (en) 2000-04-28 2009-08-11 International Business Machines Corporation Method and system for intrusion detection in a computer network
US20020069356A1 (en) * 2000-06-12 2002-06-06 Kwang Tae Kim Integrated security gateway apparatus
US7024694B1 (en) * 2000-06-13 2006-04-04 Mcafee, Inc. Method and apparatus for content-based instrusion detection using an agile kernel-based auditor
US20020032871A1 (en) * 2000-09-08 2002-03-14 The Regents Of The University Of Michigan Method and system for detecting, tracking and blocking denial of service attacks over a computer network
US9027121B2 (en) * 2000-10-10 2015-05-05 International Business Machines Corporation Method and system for creating a record for one or more computer security incidents
US20060212572A1 (en) * 2000-10-17 2006-09-21 Yehuda Afek Protecting against malicious traffic
US7150045B2 (en) * 2000-12-14 2006-12-12 Widevine Technologies, Inc. Method and apparatus for protection of electronic media
CN1295904C (en) * 2001-01-10 2007-01-17 思科技术公司 Computer security and management system
US7237264B1 (en) * 2001-06-04 2007-06-26 Internet Security Systems, Inc. System and method for preventing network misuse
US6928556B2 (en) * 2001-08-30 2005-08-09 International Business Machines Corporation Method and apparatus in a data processing system for managing situations from correlated events
US7039953B2 (en) * 2001-08-30 2006-05-02 International Business Machines Corporation Hierarchical correlation of intrusion detection events
US7331061B1 (en) * 2001-09-07 2008-02-12 Secureworks, Inc. Integrated computer security management system and method
US7197762B2 (en) * 2001-10-31 2007-03-27 Hewlett-Packard Development Company, L.P. Method, computer readable medium, and node for a three-layered intrusion prevention system for detecting network exploits
US7836503B2 (en) * 2001-10-31 2010-11-16 Hewlett-Packard Development Company, L.P. Node, method and computer readable medium for optimizing performance of signature rule matching in a network
US20030101353A1 (en) * 2001-10-31 2003-05-29 Tarquini Richard Paul Method, computer-readable medium, and node for detecting exploits based on an inbound signature of the exploit and an outbound signature in response thereto
US6546493B1 (en) * 2001-11-30 2003-04-08 Networks Associates Technology, Inc. System, method and computer program product for risk assessment scanning based on detected anomalous events
US7150043B2 (en) * 2001-12-12 2006-12-12 International Business Machines Corporation Intrusion detection method and signature table
WO2003063449A1 (en) * 2002-01-18 2003-07-31 Metrowerks Corporation System and method for monitoring network security
US7222366B2 (en) * 2002-01-28 2007-05-22 International Business Machines Corporation Intrusion event filtering
US7076803B2 (en) * 2002-01-28 2006-07-11 International Business Machines Corporation Integrated intrusion detection services

Patent Citations (80)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5008936A (en) * 1988-12-09 1991-04-16 The Exchange System Limited Partnership Backup/restore technique in a microcomputer-based encryption system
US5421006A (en) * 1992-05-07 1995-05-30 Compaq Computer Corp. Method and apparatus for assessing integrity of computer system software
US5802275A (en) * 1994-06-22 1998-09-01 Lucent Technologies Inc. Isolation of non-secure software from secure software to limit virus infection
US5970143A (en) * 1995-11-22 1999-10-19 Walker Asset Management Lp Remote-auditing of computer generated outcomes, authenticated billing and access control, and software metering system using cryptographic and other protocols
US5787409A (en) * 1996-05-17 1998-07-28 International Business Machines Corporation Dynamic monitoring architecture
US6065118A (en) * 1996-08-09 2000-05-16 Citrix Systems, Inc. Mobile code isolation cage
US5987611A (en) * 1996-12-31 1999-11-16 Zone Labs, Inc. System and methodology for managing internet access on a per application basis for client computers connected to the internet
US5948104A (en) * 1997-05-23 1999-09-07 Neuromedical Systems, Inc. System and method for automated anti-viral file update
US6816903B1 (en) * 1997-05-27 2004-11-09 Novell, Inc. Directory enabled policy management tool for intelligent traffic management
US5919257A (en) * 1997-08-08 1999-07-06 Novell, Inc. Networked workstation intrusion detection system
US5983348A (en) * 1997-09-10 1999-11-09 Trend Micro Incorporated Computer network malicious code scanner
US6272641B1 (en) * 1997-09-10 2001-08-07 Trend Micro, Inc. Computer network malicious code scanner method and apparatus
US6807583B2 (en) * 1997-09-24 2004-10-19 Carleton University Method of determining causal connections between events recorded during process execution
US5978936A (en) * 1997-11-19 1999-11-02 International Business Machines Corporation Run time error probe in a network computing environment
US6266811B1 (en) * 1997-12-31 2001-07-24 Network Associates Method and system for custom computer software installation using rule-based installation engine and simplified script computer program
US6370584B1 (en) * 1998-01-13 2002-04-09 Trustees Of Boston University Distributed routing
US5960798A (en) * 1998-02-26 1999-10-05 Fashion Nails, Inc. Method and apparatus for creating art on an object such as a person's fingernail or toenail
US6279113B1 (en) * 1998-03-16 2001-08-21 Internet Tools, Inc. Dynamic signature inspection-based network intrusion detection
US6411941B1 (en) * 1998-05-21 2002-06-25 Beeble, Inc. Method of restricting software operation within a license limitation
US6694436B1 (en) * 1998-05-22 2004-02-17 Activcard Terminal and system for performing secure electronic transactions
US6282546B1 (en) * 1998-06-30 2001-08-28 Cisco Technology, Inc. System and method for real-time insertion of data into a multi-dimensional database for network intrusion detection and vulnerability assessment
US6640248B1 (en) * 1998-07-10 2003-10-28 Malibu Networks, Inc. Application-aware, quality of service (QoS) sensitive, media access control (MAC) layer
US20020129278A1 (en) * 1998-10-15 2002-09-12 Doron Elgressy Method and system for the prevention of undesirable activities of executable objects
US6219706B1 (en) * 1998-10-16 2001-04-17 Cisco Technology, Inc. Access control for networks
US6463470B1 (en) * 1998-10-26 2002-10-08 Cisco Technology, Inc. Method and apparatus of storing policies for policy-based management of quality of service treatments of network data traffic flows
US6484203B1 (en) * 1998-11-09 2002-11-19 Sri International, Inc. Hierarchical event monitoring and analysis
US6301668B1 (en) * 1998-12-29 2001-10-09 Cisco Technology, Inc. Method and system for adaptive network security using network vulnerability assessment
US6816973B1 (en) * 1998-12-29 2004-11-09 Cisco Technology, Inc. Method and system for adaptive network security using intelligent packet analysis
US6871224B1 (en) * 1999-01-04 2005-03-22 Cisco Technology, Inc. Facility to transmit network management data to an umbrella management system
US20050193218A1 (en) * 1999-01-22 2005-09-01 Joshua Susser Techniques for permitting access across a context barrier on a small footprint device using an entry point object
US6665799B1 (en) * 1999-04-28 2003-12-16 Dvi Acquisition Corp. Method and computer software code for providing security for a computer software program
US6681331B1 (en) * 1999-05-11 2004-01-20 Cylant, Inc. Dynamic software system intrusion detection
US6466984B1 (en) * 1999-07-02 2002-10-15 Cisco Technology, Inc. Method and apparatus for policy-based management of quality of service treatments of network data traffic flows by integrating policies with application programs
US6496483B1 (en) * 1999-08-18 2002-12-17 At&T Corp. Secure detection of an intercepted targeted IP phone from multiple monitoring locations
US6501752B1 (en) * 1999-08-18 2002-12-31 At&T Corp. Flexible packet technique for monitoring calls spanning different backbone networks
US6996843B1 (en) * 1999-08-30 2006-02-07 Symantec Corporation System and method for detecting computer intrusions
US6574663B1 (en) * 1999-08-31 2003-06-03 Intel Corporation Active topology discovery in active networks
US6742015B1 (en) * 1999-08-31 2004-05-25 Accenture Llp Base services patterns in a netcentric environment
US6735702B1 (en) * 1999-08-31 2004-05-11 Intel Corporation Method and system for diagnosing network intrusion
US6952776B1 (en) * 1999-09-22 2005-10-04 International Business Machines Corporation Method and apparatus for increasing virus detection speed using a database
US7181768B1 (en) * 1999-10-28 2007-02-20 Cigital Computer intrusion detection system and method based on application monitoring
US6851057B1 (en) * 1999-11-30 2005-02-01 Symantec Corporation Data driven detection of viruses
US6892303B2 (en) * 2000-01-06 2005-05-10 International Business Machines Corporation Method and system for caching virus-free file certificates
US6957348B1 (en) * 2000-01-10 2005-10-18 Ncircle Network Security, Inc. Interoperability of vulnerability and intrusion detection systems
US6842861B1 (en) * 2000-03-24 2005-01-11 Networks Associates Technology, Inc. Method and system for detecting viruses on handheld computers
US6868062B1 (en) * 2000-03-28 2005-03-15 Intel Corporation Managing data traffic on multiple ports
US6971015B1 (en) * 2000-03-29 2005-11-29 Microsoft Corporation Methods and arrangements for limiting access to computer controlled functions and devices
US6553377B1 (en) * 2000-03-31 2003-04-22 Network Associates, Inc. System and process for maintaining a plurality of remote security applications using a modular framework in a distributed computing environment
US6751659B1 (en) * 2000-03-31 2004-06-15 Intel Corporation Distributing policy information in a communication network
US20020010771A1 (en) * 2000-05-24 2002-01-24 Davide Mandato Universal QoS adaptation framework for mobile multimedia applications
US6973577B1 (en) * 2000-05-26 2005-12-06 Mcafee, Inc. System and method for dynamically detecting computer viruses through associative behavioral analysis of runtime state
US20010052012A1 (en) * 2000-06-30 2001-12-13 Rinne Janne Petri Quality of service definition for data streams
US6879587B1 (en) * 2000-06-30 2005-04-12 Intel Corporation Packet processing in a router architecture
US7089294B1 (en) * 2000-08-24 2006-08-08 International Business Machines Corporation Methods, systems and computer program products for server based type of service classification of a communication request
US6701463B1 (en) * 2000-09-05 2004-03-02 Motorola, Inc. Host specific monitor script for networked computer clusters
US20040078467A1 (en) * 2000-11-02 2004-04-22 George Grosner Switching system
US6807156B1 (en) * 2000-11-07 2004-10-19 Telefonaktiebolaget Lm Ericsson (Publ) Scalable real-time quality of service monitoring and analysis of service dependent subscriber satisfaction in IP networks
US6996845B1 (en) * 2000-11-28 2006-02-07 S.P.I. Dynamics Incorporated Internet security analysis system and process
US7103666B2 (en) * 2001-01-12 2006-09-05 Siemens Medical Solutions Health Services Corporation System and user interface supporting concurrent application operation and interoperability
US20070043631A1 (en) * 2001-01-29 2007-02-22 Cline Linda S Extensible network services system
US7136908B2 (en) * 2001-01-29 2006-11-14 Intel Corporation Extensible network services system
US20020103720A1 (en) * 2001-01-29 2002-08-01 Cline Linda S. Extensible network services system
US20020120853A1 (en) * 2001-02-27 2002-08-29 Networks Associates Technology, Inc. Scripted distributed denial-of-service (DDoS) attack discrimination using turing tests
US20020143914A1 (en) * 2001-03-29 2002-10-03 Cihula Joseph F. Network-aware policy deployment
US20020143911A1 (en) * 2001-03-30 2002-10-03 John Vicente Host-based network traffic control system
US20020194317A1 (en) * 2001-04-26 2002-12-19 Yasusi Kanada Method and system for controlling a policy-based network
US20030126468A1 (en) * 2001-05-25 2003-07-03 Markham Thomas R. Distributed firewall system and method
US20030159070A1 (en) * 2001-05-28 2003-08-21 Yaron Mayer System and method for comprehensive general generic protection for computers against malicious programs that may steal information and/or cause damages
US7171688B2 (en) * 2001-06-25 2007-01-30 Intel Corporation System, method and computer program for the detection and restriction of the network activity of denial of service attack software
US7069330B1 (en) * 2001-07-05 2006-06-27 Mcafee, Inc. Control of interaction between client computer applications and network resources
US7225430B2 (en) * 2001-07-26 2007-05-29 Landesk Software Limited Software code management method and apparatus
US6832260B2 (en) * 2001-07-26 2004-12-14 International Business Machines Corporation Methods, systems and computer program products for kernel based transaction processing
US6826716B2 (en) * 2001-09-26 2004-11-30 International Business Machines Corporation Test programs for enterprise web applications
US20030084323A1 (en) * 2001-10-31 2003-05-01 Gales George S. Network intrusion detection system and method
US7065790B1 (en) * 2001-12-21 2006-06-20 Mcafee, Inc. Method and system for providing computer malware names from multiple anti-virus scanners
US20030149888A1 (en) * 2002-02-01 2003-08-07 Satyendra Yadav Integrated network intrusion detection
US7174566B2 (en) * 2002-02-01 2007-02-06 Intel Corporation Integrated network intrusion detection
US20030149887A1 (en) * 2002-02-01 2003-08-07 Satyendra Yadav Application-specific network intrusion detection
US20030200439A1 (en) * 2002-04-17 2003-10-23 Moskowitz Scott A. Methods, systems and devices for packet watermarking and efficient provisioning of bandwidth
US20030204596A1 (en) * 2002-04-29 2003-10-30 Satyendra Yadav Application-based network quality of service provisioning

Cited By (29)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10044738B2 (en) 2002-02-01 2018-08-07 Intel Corporation Integrated network intrusion detection
US20100122317A1 (en) * 2002-02-01 2010-05-13 Satyendra Yadav Integrated Network Intrusion Detection
US8752173B2 (en) 2002-02-01 2014-06-10 Intel Corporation Integrated network intrusion detection
US7761915B2 (en) * 2005-12-28 2010-07-20 Zyxel Communications Corp. Terminal and related computer-implemented method for detecting malicious data for computer network
US20070147239A1 (en) * 2005-12-28 2007-06-28 Chun-Te Wu Terminal and Related Computer-Implemented Method for Detecting Malicious Data for Computer Network
US20080313738A1 (en) * 2007-06-15 2008-12-18 Broadcom Corporation Multi-Stage Deep Packet Inspection for Lightweight Devices
US7853689B2 (en) * 2007-06-15 2010-12-14 Broadcom Corporation Multi-stage deep packet inspection for lightweight devices
US9762546B2 (en) * 2013-06-27 2017-09-12 Jeong Hoan Seo Multi-connection system and method for service using internet protocol
US20160173452A1 (en) * 2013-06-27 2016-06-16 Jeong Hoan Seo Multi-connection system and method for service using internet protocol
US9407602B2 (en) * 2013-11-07 2016-08-02 Attivo Networks, Inc. Methods and apparatus for redirecting attacks on a network
US20150128246A1 (en) * 2013-11-07 2015-05-07 Attivo Networks Inc. Methods and apparatus for redirecting attacks on a network
US11625485B2 (en) 2014-08-11 2023-04-11 Sentinel Labs Israel Ltd. Method of malware detection and system thereof
US11886591B2 (en) 2014-08-11 2024-01-30 Sentinel Labs Israel Ltd. Method of remediating operations performed by a program and system thereof
US11616812B2 (en) 2016-12-19 2023-03-28 Attivo Networks Inc. Deceiving attackers accessing active directory data
US11695800B2 (en) 2016-12-19 2023-07-04 SentinelOne, Inc. Deceiving attackers accessing network data
US11716341B2 (en) 2017-08-08 2023-08-01 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US11838306B2 (en) 2017-08-08 2023-12-05 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US11716342B2 (en) 2017-08-08 2023-08-01 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US11722506B2 (en) 2017-08-08 2023-08-08 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US11876819B2 (en) 2017-08-08 2024-01-16 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US11838305B2 (en) 2017-08-08 2023-12-05 Sentinel Labs Israel Ltd. Methods, systems, and devices for dynamically modeling and grouping endpoints for edge networking
US10587521B2 (en) * 2017-11-07 2020-03-10 Facebook, Inc. Hierarchical orchestration of a computer network
US20190140958A1 (en) * 2017-11-07 2019-05-09 Facebook, Inc. Hierarchical orchestration of a computer network
US11888897B2 (en) 2018-02-09 2024-01-30 SentinelOne, Inc. Implementing decoys in a network environment
US11580218B2 (en) 2019-05-20 2023-02-14 Sentinel Labs Israel Ltd. Systems and methods for executable code detection, automatic feature extraction and position independent code detection
US11790079B2 (en) 2019-05-20 2023-10-17 Sentinel Labs Israel Ltd. Systems and methods for executable code detection, automatic feature extraction and position independent code detection
US11748083B2 (en) 2020-12-16 2023-09-05 Sentinel Labs Israel Ltd. Systems, methods and devices for device fingerprinting and automatic deployment of software in a computing network using a peer-to-peer approach
US11579857B2 (en) 2020-12-16 2023-02-14 Sentinel Labs Israel Ltd. Systems, methods and devices for device fingerprinting and automatic deployment of software in a computing network using a peer-to-peer approach
US11899782B1 (en) 2021-07-13 2024-02-13 SentinelOne, Inc. Preserving DLL hooks

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