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International Symposium on Security in Computing and Communication

SSCC 2018: Security in Computing and Communications pp 563–577Cite as

A Comparative Analysis of Different Soft Computing Techniques for Intrusion Detection System

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 969))

Abstract

In this internet era, the data are flooded with malicious activities. The role of soft computing techniques to classify highly vulnerable, complex and uncertain network data by devising an intrusion detection system is so significant. The proposed work emphasizes on the classification of normal and anomaly packets in the networks by carrying out the comparative performance evaluation of different soft computing tools including Genetic Programming (GP), Fuzzy logic, Artificial neural network (ANN) and Probabilistic model with Clustering methods using NSL-KDD dataset. Here, Fuzzy logic runs the first place in the performance metrics and the clustering algorithms and Genetic programming deliver the worst performances. Fuzzy Unordered Rule Induction Algorithm (FURIA) in Fuzzy logic gives a high detection rate of accuracy (99.69%) with the low rate of false alarms (0.31%). The computational time of FURIA (78.14 s) is not so expectant. So Fuzzy Rough Nearest Neighbor(FRNN) is recommended as an optimistic model with a sensible accuracy rate of 99.51% and tolerable false alarm rate of 0.49% along with a pretty good computational time of 0.33 s.

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Authors and Affiliations

  1. Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India

    Josy Elsa Varghese & Balachandra Muniyal

Authors
  1. Josy Elsa Varghese
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  2. Balachandra Muniyal
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Corresponding authors

Correspondence to Josy Elsa Varghese or Balachandra Muniyal .

Editor information

Editors and Affiliations

  1. Technology and Management, Indian Institute of Information, Kerala, India

    Sabu M. Thampi

  2. Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA

    Sanjay Madria

  3. Guangzhou University, Guangzhou, China

    Guojun Wang

  4. Howard University, Washington, DC, USA

    Danda B. Rawat

  5. University of the West of Scotland, Paisley, Glasgow, UK

    Jose M. Alcaraz Calero

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Varghese, J.E., Muniyal, B. (2019). A Comparative Analysis of Different Soft Computing Techniques for Intrusion Detection System. In: Thampi, S., Madria, S., Wang, G., Rawat, D., Alcaraz Calero, J. (eds) Security in Computing and Communications. SSCC 2018. Communications in Computer and Information Science, vol 969. Springer, Singapore. https://doi.org/10.1007/978-981-13-5826-5_44

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  • DOI: https://doi.org/10.1007/978-981-13-5826-5_44

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5825-8

  • Online ISBN: 978-981-13-5826-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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