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Immune Algorithm Optimization of Membership Functions for Mining Association Rules

  • Hongwei Mo
  • Xiquan Zuo
  • Lifang Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4222)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hongwei Mo
    • 1
  • Xiquan Zuo
    • 2
  • Lifang Xu
    • 1
  1. 1.Automation CollegeHarbin Engineering UniversityHarbinChina
  2. 2.College of Computer Science and TechnologyBeijing University of Posts and TelecommunicationsBeijingChina

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