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Evolutionary and Swarm Intelligence Algorithms pp 169–190Cite as

Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 779))

Abstract

The so-called Evolutionary Fuzzy Systems consists of the application of evolutionary algorithms in the design process of fuzzy systems. Thanks to this hybridization, excellent abilities are provided to fuzzy systems in different work scenarios of data mining, such as standard classification, regression problems and association rule mining. The main reason of their success is the adaptation of their inner characteristics to any context. Among different areas of application, Evolutionary Fuzzy Systems have recently excelled in the area of Intrusion Detection Systems, yielding both accurate and interpretable models. To fully understand the nature and goodness of these type of models, we will introduce a full taxonomy on Evolutionary Fuzzy Systems. Then, we will overview a number of proposals from this research area that have been developed to address Intrusion Detection Systems. Finally, we will present a case study highlighting the good behaviour of Evolutionary Fuzzy Systems in this particular context.

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Authors and Affiliations

  1. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    S. Elhag

  2. Department of Computer Science and Artificial Intelligence, University of Granada, 18071, Granada, Spain

    A. Fernández & F. Herrera

  3. Faculty of Computing and Information Technology, University of Jeddah, Jeddah, 21589, Saudi Arabia

    S. Alshomrani

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  1. S. Elhag
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  2. A. Fernández
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  3. S. Alshomrani
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  4. F. Herrera
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Correspondence to S. Elhag .

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Editors and Affiliations

  1. South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

  2. ABV-Indian Institute of Information Technology and Management, Gwalior, Madhya Pradesh, India

    Pramod Kumar Singh

  3. Electronics and Communication Sciences Unit (ECSU), Indian Statistical Institute, Kolkata, West Bengal, India

    Nikhil R. Pal

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Elhag, S., Fernández, A., Alshomrani, S., Herrera, F. (2019). Evolutionary Fuzzy Systems: A Case Study for Intrusion Detection Systems. In: Bansal, J., Singh, P., Pal, N. (eds) Evolutionary and Swarm Intelligence Algorithms. Studies in Computational Intelligence, vol 779. Springer, Cham. https://doi.org/10.1007/978-3-319-91341-4_9

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