Information Assurance in Computer Networks: Methods, Models by Dipankar Dasgupta, Fabio A. Gonzalez (auth.), Vladimir I.

By Dipankar Dasgupta, Fabio A. Gonzalez (auth.), Vladimir I. Gorodetski, Victor A. Skormin, Leonard J. Popyack (eds.)

This e-book provides the refereed lawsuits of the foreign Workshop on Mathematical equipment, types, and Architectures for community safeguard platforms, MMM-ACNS 2001, held in St. Petersburg in may perhaps 2001.
The 24 revised complete papers offered including 5 invited contributions have been rigorously reviewed and chosen from 36 submissions. The papers are prepared in topical sections on community safety structures: foundations, versions and architectures; intrusion detection: foundations and types; entry keep watch over, authentication, and authorization; and cryptography and steganography: mathematical foundation, protocols, and utilized methods.

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Extra resources for Information Assurance in Computer Networks: Methods, Models and Architectures for Network Security International Workshop MMM-ACNS 2001 St. Petersburg, Russia, May 21–23, 2001 Proceedings

Example text

However, the majority of known research using the multiagent model of IDS and computer network security system on a whole only considers the simplified version of agents’ architecture and their cooperative behavior and do not employ the capabilities of multi-agent technology. In particular, the proposed models and architectures use agents at the pre-processing phase of the protection task. Here the agents are not knowledge-based, managed by a high-level software manager, restricted by solving intrusion detection task and do not interact with the access Agent-Based Model of Computer Network Security System 41 control and other security system components.

U 1/ and U 2/ have the function g: Z ™ Q “ X, where Q is some finite set. The restoration of the message z is determined by a condition, that for any z ³ Z, q ³ Q, g -1 (g (z, q )) = z.. (4) 18 A. Grusho The choice of q is defined by a conditional distribution P Q (q | z). Then the distribution P(z, q) on Z ™Q and the function g(z, q) define a probability measure PX/ (x) on •. Measures PX and PX/ may be different. Probability measure PX/ (x) and function l(x) determine a probability measure Q / (y) on set Y.

While monitoring the input traffic, IDS detects events, patterns consisting of the predefined sequences of events. The detected patterns form input facts of knowledge-based components of IDS responsible for the intrusion detection. These components make decisions on the basis of rules, whose truth-values depend on input facts (detected patterns). Using IDS allows to improve integrity and efficiency of the security system as a whole, on-line monitoring of users’ activity, recognition of, notification about and, possibly, fixing corrupted system files and data as well as system configuration altering, etc.

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