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A hybrid method consisting of GA and SVM for intrusion detection system

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Abstract

In this paper, a hybrid method of support vector machine and genetic algorithm (GA) is proposed and its implementation in intrusion detection problem is explained. The proposed hybrid algorithm is employed in reducing the number of features from 45 to 10. The features are categorized into three priorities using GA algorithm as the highest important is the first priority and the lowest important is placed in the third priority. The feature distribution is done in a way that 4 features are placed in the first priority, 4 features in the second, and 2 features in the third priority. The results reveal that the proposed hybrid algorithm is capable of achieving a true-positive value of 0.973, while the false-positive value is 0.017.

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Authors and Affiliations

  1. Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, VIC 3122, Australia

    R. Rahmani

  2. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Johor Bahru, Malaysia

    B. M. Aslahi-Shahri & A. Ebrahimi

  3. Department of Electrical & Computer, College of Engineering, Yadegare -e- Imam Khomeini (RAH) Branch, Islamic Azad University, Tehran, Iran

    M. Chizari

  4. Department of E-Commerce, College of E-Learning, Shiraz University, Shiraz, Iran

    A. Maralani

  5. Department of Electrical & Computer Engineering, Payam Noor University (PNU), Tehran, Iran

    M. Eslami & M. J. Golkar

Authors
  1. B. M. Aslahi-Shahri
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  2. R. Rahmani
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  3. M. Chizari
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  4. A. Maralani
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  5. M. Eslami
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  6. M. J. Golkar
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  7. A. Ebrahimi
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Correspondence to R. Rahmani.

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Aslahi-Shahri, B.M., Rahmani, R., Chizari, M. et al. A hybrid method consisting of GA and SVM for intrusion detection system. Neural Comput & Applic 27, 1669–1676 (2016). https://doi.org/10.1007/s00521-015-1964-2

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  • DOI: https://doi.org/10.1007/s00521-015-1964-2

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