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A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation (Paperback) Loot Price: R1,367
Discovery Miles 13 670
A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation (Paperback): David L...

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation (Paperback)

David L Hancock

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Loot Price R1,367 Discovery Miles 13 670 | Repayment Terms: R128 pm x 12*

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The rising sophistication of cyber threats as well as the improvement of physical computer network properties present increasing challenges to contemporary Intrusion Detection (ID) techniques. To respond to these challenges, a multi agent system (MAS) coupled with flow-based ID techniques may effectively complement traditional ID systems. This paper develops: 1) a scalable software architecture for a new, self-organized, multi agent, flow-based ID system; and 2) a network simulation environment suitable for evaluating implementations of this MAS architecture and for other research purposes. Self-organization is achieved via 1) a "reputation" system that influences agent mobility in the search for effective vantage points in the network; and 2) multi objective evolutionary algorithms that seek effective operational parameter values. This paper illustrates, through quantitative and qualitative evaluation, 1) the conditions for which the reputation system provides a significant benefit; and 2) essential functionality of a complex network simulation environment supporting a broad range of malicious activity scenarios. These results establish an optimistic outlook for further research in flow-based multi agent systems for ID in computer networks.

General

Imprint: Biblioscholar
Country of origin: United States
Release date: October 2012
First published: October 2012
Authors: David L Hancock
Dimensions: 246 x 189 x 10mm (L x W x T)
Format: Paperback - Trade
Pages: 182
ISBN-13: 978-1-249-58665-4
Categories: Books > Social sciences > Education > General
LSN: 1-249-58665-8
Barcode: 9781249586654

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