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International Conference on Information Security and Cryptology

Inscrypt 2006: Information Security and Cryptology pp 153–167Cite as

Survey and Taxonomy of Feature Selection Algorithms in Intrusion Detection System

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 4318))

Abstract

The Intrusion detection system deals with huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. Feature selection, therefore, is an important issue in intrusion detection. In this paper we introduce concepts and algorithms of feature selection, survey existing feature selection algorithms in intrusion detection systems, group and compare different algorithms in three broad categories: filter, wrapper, and hybrid. We conclude the survey by identifying trends and challenges of feature selection research and development in intrusion detection system.

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Author information

Authors and Affiliations

  1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100080

    You Chen, Yang Li, Xue-Qi Cheng & Li Guo

  2. Graduate School of the Chinese Academy of Sciences, Beijing, 100039

    You Chen & Yang Li

Authors
  1. You Chen
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  2. Yang Li
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  3. Xue-Qi Cheng
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  4. Li Guo
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Editor information

Editors and Affiliations

  1. University College London, UK

    Helger Lipmaa

  2. Computer Science Department, Google Inc. and Columbia University, 1214 Amsterdam Avenue, 10027, New York, NY, USA

    Moti Yung

  3. SKLOIS Lab, Institute of Software, Chinese Academy of Sciences, 100080, Beijing, P.R. China

    Dongdai Lin

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© 2006 Springer-Verlag Berlin Heidelberg

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Chen, Y., Li, Y., Cheng, XQ., Guo, L. (2006). Survey and Taxonomy of Feature Selection Algorithms in Intrusion Detection System. In: Lipmaa, H., Yung, M., Lin, D. (eds) Information Security and Cryptology. Inscrypt 2006. Lecture Notes in Computer Science, vol 4318. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11937807_13

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  • DOI: https://doi.org/10.1007/11937807_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49608-3

  • Online ISBN: 978-3-540-49610-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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