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Comparative Performance Analysis of Negative Selection Algorithm with Immune and Classification Algorithms

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Recent Advances on Soft Computing and Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 287))

Abstract

The ability of Negative Selection Algorithm (NSA) to solve a number of anomaly detection problems has proved to be effective. This paper thus presents an experimental study of negative selection algorithm with some classification algorithms. The purpose is to ascertain their efficiency rates in accurately detecting abnormalities in a system when tested with well-known datasets. Negative selection algorithm with some selected immune and classifier algorithms are used for experimentation and analysis. Three different datasets have been acquired for this task and a comparison performance executed. The empirical results illustrates that the artificial immune system of negative selection algorithm can achieve highest detection and lowest false alarm. Thus, it signifies the suitability and potentiality of NSA for discovering unusual changes in normal behavioral flow.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Batu Pahat, Johor, Malaysia

    Ayodele Lasisi & Rozaida Ghazali

  2. Faculty of Computer Science and Information Technology, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Tutut Herawan

Authors
  1. Ayodele Lasisi
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  2. Rozaida Ghazali
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  3. Tutut Herawan
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Corresponding author

Correspondence to Ayodele Lasisi .

Editor information

Editors and Affiliations

  1. Department of Information System Faculty of Comp. Sci. & Info. Tech., University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Faculty of Comp. Sci. and Info. Tech, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia

    Rozaida Ghazali

  3. Faculty of Comp. Sci. and Info. Tech., Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia

    Mustafa Mat Deris

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© 2014 Springer International Publishing Switzerland

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Lasisi, A., Ghazali, R., Herawan, T. (2014). Comparative Performance Analysis of Negative Selection Algorithm with Immune and Classification Algorithms. In: Herawan, T., Ghazali, R., Deris, M. (eds) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-07692-8_42

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  • DOI: https://doi.org/10.1007/978-3-319-07692-8_42

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07691-1

  • Online ISBN: 978-3-319-07692-8

  • eBook Packages: EngineeringEngineering (R0)

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