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A Survey of Feature Selection Techniques in Intrusion Detection System: A Soft Computing Perspective

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Book cover Progress in Computing, Analytics and Networking

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 710))

Abstract

In the process of detecting different kinds of attacks in anomaly-based intrusion detection system (IDS), both normal and attack data are profiled with the help of selected attributes. Various types of attributes are collected to create the attack and normal traffic patterns. Some of the attributes are derived from protocol header fields, and some of them represent continuous information profiled over a period. “Curse of Dimensionality” is one of the major issues in IDS. The computational complexity of the model generation and classification time of IDS is directly proportional to the number of attributes of the profile. In a typical IDS preprocessing stage, more significant features among the available features are selected. This paper presents a brief taxonomy of several feature selection methods with emphasis on soft computing techniques, viz., rough sets, fuzzy rough sets, and ant colony optimization.

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Authors and Affiliations

  1. MVGR College of Engineering, Vizianagaram, Andhra Pradesh, India

    P. Ravi Kiran Varma

  2. Andhra University College of Engineering, Visakhapatnam, Andhra Pradesh, India

    V. Valli Kumari

  3. University College of Engineering Kakinada, JNT University, Kakinada, Andhra Pradesh, India

    S. Srinivas Kumar

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  1. P. Ravi Kiran Varma
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  2. V. Valli Kumari
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  3. S. Srinivas Kumar
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Correspondence to P. Ravi Kiran Varma .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  2. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Siddharth Swarup Rautaray

  3. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Himansu Das

  4. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

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Ravi Kiran Varma, P., Valli Kumari, V., Srinivas Kumar, S. (2018). A Survey of Feature Selection Techniques in Intrusion Detection System: A Soft Computing Perspective. In: Pattnaik, P., Rautaray, S., Das, H., Nayak, J. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-7871-2_75

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  • DOI: https://doi.org/10.1007/978-981-10-7871-2_75

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