Immune algorithm optimization of membership functions for mining association rules

Authors:
Hongwei Mo;Xiquan Zuo;Lifang Xu
Affiliations:
Automation College, Harbin Engineering University, Harbin, China;College of Computer Science and Technology, Beijing University of Posts and Telecommunications, Beijing, China;Automation College, Harbin Engineering University, Harbin, China
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part II
Year:
2006

Citing 8
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Abstract

In the paper, immune algorithm(IA) is proposed for optimizing membership function of fuzzy variables for mining associate rules. It is used in network detection to testify its efficiency in such mining task, including maximizing the similarity between normal association rule sets while minimizing the similarity between a normal and an abnormal association rule set. Experiment results show that IA-optimization based fuzzy logic system can improve the performance of mining associate rules in network intrusion.