Alert Fusion for a Computer Host Based Intrusion Detection System

Authors:
Chuan Feng;Jianfeng Peng;Haiyan Qiao;Jerzy W. Rozenblit
Affiliations:
The University of Arizona, USA;The University of Arizona, USA;The University of Arizona, USA;The University of Arizona, USA
Venue:
ECBS '07 Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
Year:
2007

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Cited 2

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A program-based anomaly intrusion detection scheme using multiple detection engines and fuzzy inference

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Abstract

Intrusions impose tremendous threats to today's computer hosts. Intrusions using security breaches to achieve unauthorized access or misuse of critical information can have catastrophic consequences. To protect computer hosts from the increasing threat of intrusion, various kinds of Intrusion Detection Systems (IDSs) have been developed. The main disadvantages of current IDSs are a high false detection rate and the lack of post-intrusion decision support capability. To minimize these drawbacks, we propose an event-driven intrusion detection architecture which integrates Subject-Verb-Object (SVO) multi-point monitors and an impact analysis engine. Alert fusion and verification models are implemented to provide more reasonable intrusion information from incomplete, inconsistent or imprecise alerts acquired by SVO monitors. DEVS formalism is used to describe the model based design approach. Finally we use the DEVS-JAVA simulation tool to show the feasibility of the proposed system.