Staniford-Chen, S, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip, D. Zerkle (1996), "GrIDS - A Graph Based Intrusion Detection System for Large Networks, NISSC, http://olympus.cs.ucdavis.edu/arpa/grids/welcome.html  Home/Search   Document Not in Database   Summary   Related Articles   Check

.... profiles of network routing and management protocols and monitors the execution of protocols in routers and switches to recognize deviations from the normal profile [9] SRI s Emerald system is a combination anomaly and misuse detection system [17] UC Davis has developed a prototype called GrIDS [22] that uses a graph based approach to detect anomalous activities on host computers and network traffic between them. Most of these IDSs work by examining patterns of system calls or network traffic. In almost every case, the IDS is working on behalf but completely independent of the applications, ....

S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip, and D. Zerkle. GrIDS-a graph based intrusion detection system for large networks. In Proceedings of the 19th National Information Systems Security Conference, September 1996.

.... Correctness preserving mapping Correctness preserving translation Mobile Agents Distributed Implementation Prototyped Box is focus of this paper Present Figure 1: IDS development process 4 A B C D E Figure 2: Beginning of a worm graph, and the graph after the worm has spread [24] 2.1 GrIDS The Graph Based Intrusion Detection System (GrIDS) dynamically builds graphs describing network activity by applying user de ned rules to audit data [24] In GrIDS graphs, nodes represent hosts or aggregations of hosts and edges represent network activity. Rather than building a ....

....Figure 1: IDS development process 4 A B C D E Figure 2: Beginning of a worm graph, and the graph after the worm has spread [24] 2. 1 GrIDS The Graph Based Intrusion Detection System (GrIDS) dynamically builds graphs describing network activity by applying user de ned rules to audit data [24]. In GrIDS graphs, nodes represent hosts or aggregations of hosts and edges represent network activity. Rather than building a single graph including all system activity, individual graphs are maintained by rule sets. Each rule set matches certain events from the network audit trail and either ....

S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip, and D. Zerkle. GrIDS-a graph based intrusion detection system for large networks. In 19th National Information Systems Security Conference Proceedings, pages 361370, October 1996.

....modeling techniques for IDS exist, but they model the intrusion detection system rather than the intrusion itself. For example, GrIDS, the Graph based Intrusion Detection System, detects misuse in a system by dynamically building graphs that model the communication activities in a network [22]. The graph depends on user de ned rules to identify suspicious patterns and models intrusion detection, rather than intrusions. ARMD, the Adaptable Real time Misuse Detection system, represents misuse signatures as directed acyclic graphs [16] Unlike the object event model used by GrIDS, the ....

Staniford-Chen, S., Cheung, S., Crawford, R., Dilger, M., Frank, J., Hoagland, J., Levitt, K., Wee, C., Yip, R., and Zerkle, D. GrIDS-a graph based intrusion detection system for large networks. In 19th National Information Systems Security Conference Proceedings (Oct. 1996), pp. 361370.

....network intrusion and misuse. Most approaches use signature matching to detect known attacks and statistical anomaly detection for novel attacks. Among many others, examples include the IDES, NIDES, and EMERALD systems from Stanford Research Institute (SRI) 1] 6] the GrIDS system from UC Davis [10] which constructs activity graphs of network operations to look for traffic patterns indicative of coordinated attacks on a network; the JiNao system from North Carolina State University and MCNC [7] which uses statistical anomaly detection and signature matching to detect attacks on routing ....

S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip, and D. Zerkle. Grids--a graph based intrusion detection system for large networks. In Proceedings of the National Information Systems Security Conference, pages 361--370, October, 1996.

....then feeds into a centralized analysis process, which employs one or more different detection techniques. While this architecture is effective for small collections of monitored hosts, centralized analysis limits the ability to scale up to handle larger collections. Subsequent generations of IDSs [Chen96] address scalability mainly by introducing intermediate components that preprocess and consolidate information obtained by the collection process for input into the analysis process. Nearly all present day commercial IDSs follow a hierarchical architecture. Information gathering occurs at leaf ....

S. Staniford-Chen, et ali., "GrIDS -- A Graph Based Intrusion Detection System For Large Networks," National Computer Security Conference, October 1992.

....from event generators. A large portion of intrusion detection research goes into creating new ways to analyze event streams to extract relevant information, and a number of different approaches have been studied. Event analysis techniques based on statistical anomaly detection[2] graph analysis[3], and even biological immune system models[4] have been proposed. E boxes and A boxes can produce large quantities of data. This information must be made available to the system s operators if it is to be of any use. The D box component of an IDS defines the means used to store security ....

S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip and D. Zerkle, "GrIDS -- A GraphBased Intrusion Detection System for Large Networks," In The 19th National Information Systems Security Conference, 1996.

....single IDS at any level of monitoring area performs local analysis and sends its local analysis results up to the IDS at the next level in the hierarchy. Thus, IDS s at higher levels only need to analyse transferred local reports collectively. The Graph based Intrusion Detection System (GrIDS) [10] and Event Monitoring Enabling Responses to Anomalous Live Disturbances (EMERALD) 8] project propose this approach to monitor largescale networks and they are still in progress. The hierarchical approach seems to show better scalability by allowing local analyses at distributed local monitoring ....

Staniford-Chen, S., et al., 1996, "GrIDS -- A Graph-Based Intrusion Detection System for Large Networks", Proceeding of the 19th National Information Systems Security Conference. http://seclab.cs.ucdavis.edu/papers.html

.... from ISS, Intruder Alert from Axent, Net Ranger from Wheelgroup, and Stalker from Network Associates [1] 2] 3] 4] Advanced research products under development include Network Radar from Net Squared, EMERALD from SRI, and MIDS and GRIDS from the University of California at Davis [5] 6] 7] [8]. Many useful and free research products are available: tripwire, COPS, SPINet, DoSTracker, and NIDES [9] 10] 11] 12] 13] Anomaly based IDRSs, like NIDES and EMERALD 2 , detect anomalous activity on a host or in a network. Anomaly detectors have high false positive rates because anomaly ....

....a small signature at a network interface that they are undetectable. These attacks require a distributed detection system that collects and aggregates data from many sites. The UC Davis GRIDS system is one such system. However, none of these systems have addressed where to respond to such attacks [8]. Dealing with Imprecise Intrusion Detection Our model assumes that security servers can detect attacks with one hundred percent accuracy. While this is convenient for designing formal models, in practice it is simply not true. Can one extend the policy template to include the certainty an IDRS ....

: S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K. Levitt, C. Wee, R. Yip, D. Zerkle. GRIDS - A Graph-Based Intrusion Detection System for Large Networks, The 19 th National Information Systems Security Conference.

.... Computer Science Department Email: fvincent,bhorling,wagner,lesserg cs.umass.edu UMass Computer Science Technical Report 1997 60 October 16, 1997 Abstract The growth of a distributed processing system can increase both the number and likelihood of attacks it may be subject to over its lifetime [14, 7]. This fact, in addition to the complexity inherent in such an environment, makes the survivability of large heterogeneous systems one of the most challenging research areas currently being investigated[1] Our goal is to create a distributed simulation system to test various coordination ....

.... environment is giving rise to the next generation of powerful applications, the same decentralized networked characteristics that serve as the growth catalyst also create the greatest hazard to these applications, that is the vulnerability of these applications to attack from outside sources [14, 7]. Applications that are open, or built from individual components that are themselves open systems, are susceptible to virus style attacks and to attacks that disable the network, block communication, or disable member applications. Attacks may be deliberate, i.e. the action of an adversary, or ....

S. Staniford-Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, Hoagland J., K. Levitt, C. Wee, R. Yip, and D. Zerkle. Grids-a graph based intrusion detection system for large networks. Technical report, NISSC, 1996. http://seclab.cs.ucdavis.edu/arpa/- grids/welcome.html.

No context found.

Stuart Staniford-Chen, Steven Cheung, Richard Crawford, Mark Dilger, Jeremy Frank, James Hoagland, Karl Levitt, Christopher Wee, Raymond Yip, and Dan Zerkle. GrIDS-A graph based intrusion detection system for large networks. In Proceedings of the 19th National Information Systems Security Conference, 1996.

No context found.

S. Stani ford Chen, S. Cheung, R. Crawford, M. Dilger, J. Frank, J. Hoagland, K Levitt, C. Wee, R. Yip, and D. Zerkle. GrIDS---A graph based intrusion detection system for large networks. In Proceedings of the 19th National Information Systems Security Conference, 1996.

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