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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Agent Based Intrusion Detection with Soft Evidence

Agent Based Intrusion Detection with Soft Evidence
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Author(s): V. Gowadia (University of South Carolina, USA), C. Farkas (University of South Carolina, USA) and M. Valtorta (University of South Carolina, USA)
Copyright: 2003
Pages: 4
Source title: Information Technology & Organizations: Trends, Issues, Challenges & Solutions
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-066-0.ch037
ISBN13: 9781616921248
EISBN13: 9781466665330

Abstract

In this paper we propose a new framework for intrusion detection, called Probabilistic Agent-Based Intrusion Detection (PAID), using agent encapsulated Bayesian networks. It allows agents to share their beliefs, i.e., the calculated probability distribution of event occurrence. A unique feature of our model is that the agents use the soft evidential update method to process beliefs. This provides a continuous scale for intrusion detection, supports merging of signature based and anomaly based systems, and reduces the communication overhead in a distributed intrusion detection scenario. We have developed a FIPA compliant agent communication architecture that provides a prototype implementation.

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