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Immune Algorithm Optimization of Membership Functions for Mining Association Rules

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Advances in Natural Computation (ICNC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4222))

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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.

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Author information

Authors and Affiliations

  1. Automation College, Harbin Engineering University, 150001, Harbin, China

    Hongwei Mo & Lifang Xu

  2. College of Computer Science and Technology, Beijing University of Posts and Telecommunications, 100080, Beijing, China

    Xiquan Zuo

Authors
  1. Hongwei Mo
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  2. Xiquan Zuo
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  3. Lifang Xu
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Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., P.O. Box, 710071, Xi’an, P.R. China

    Xinbo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

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© 2006 Springer-Verlag Berlin Heidelberg

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Mo, H., Zuo, X., Xu, L. (2006). Immune Algorithm Optimization of Membership Functions for Mining Association Rules. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_12

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  • DOI: https://doi.org/10.1007/11881223_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45907-1

  • Online ISBN: 978-3-540-45909-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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