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Anomaly intrusion detection using multi-objective genetic fuzzy system and agent-based evolutionary computation framework

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3 Author(s)
Chi-Ho Tsang ; Dept. of Comput. Sci., Hong Kong City Univ., Kowloon, China ; Sam Kwong ; Hanli Wang

In this paper, we present a multi-objective genetic fuzzy system for anomaly intrusion detection. The proposed system extracts accurate and interpret able 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.

Published in:

Data Mining, Fifth IEEE International Conference on

Date of Conference:

27-30 Nov. 2005