Anomaly Intrusion Detection Using Multi-Objective Genetic Fuzzy System and Agent-Based Evolutionary Computation Framework

Authors:
Chi-Ho Tsang;Sam Kwong;Hanli Wang
Affiliations:
City University of Hong Kong;City University of Hong Kong;City University of Hong Kong
Venue:
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Year:
2005

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Abstract

In this paper, we present a multi-objective genetic fuzzy system for anomaly intrusion detection. The proposed system extracts accurate and interpretable fuzzy rule-based knowledge from network data using an agent-based evolutionary computation framework. The experimental results on KDD-Cup99 intrusion detection benchmark data demonstrate that our system can achieve high detection rate for intrusion attacks and low false positive rate for normal network traffic.