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An Intelligent Agent Based Intrusion Detection System Using Fuzzy Rough Set Based Outlier Detection

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Soft Computing Techniques in Vision Science

Part of the book series: Studies in Computational Intelligence ((SCI,volume 395))

Abstract

Since existing Intrusion Detection Systems (IDS) including misuse detection and anomoly detection are generally incapable of detecting new type of attacks. However, all these systems are capable of detecting intruders with high false alarm rate. It is an urgent need to develop IDS with very high Detection rate and with low False alarm rate. To satisfy this need we propose a new intelligent agent based IDS using Fuzzy Rough Set based outlier detection and Fuzzy Rough set based SVM. In this proposed model we intorduced two different inteligent agents namely feature selection agent to select the required feature set using fuzzy rough sets and decision making agent manager for making final decision. Moreover, we have introduced fuzzy rough set based outlier detection algorithm to detect outliers. We have also adopted Fuzzy Rough based SVM in our system to classify and detect anomalies efficiently. Finally, we have used KDD Cup 99 data set for our experiment, the experimental result show that the proposed intelligent agent based model improves the overall accuracy and reduces the false alarm rate.

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Authors and Affiliations

  1. Department of Information Science and Technology, College of Engineering Guindy, Anna University, Chennai, 25, India

    N. Jaisankar, S. Ganapathy, P. Yogesh & A. Kannan

  2. KTH University, Stockholm, Swedan

    K. Anand

Authors
  1. N. Jaisankar
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  2. S. Ganapathy
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  3. P. Yogesh
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  4. A. Kannan
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  5. K. Anand
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Corresponding author

Correspondence to N. Jaisankar .

Editor information

Editors and Affiliations

  1. , Computer Science and Engineering, SOA University, Bhubaneswar, 752 024, India

    Srikanta Patnaik

  2. , School of Electronic Engineering, Kumoh National Institute of Technology, Yahoho-dong, Gyeongbuk 1, Gumi, 730-701, Korea, Republic of (South Korea)

    Yeon-Mo Yang

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© 2012 Springer-Verlag Berlin Heidelberg

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Jaisankar, N., Ganapathy, S., Yogesh, P., Kannan, A., Anand, K. (2012). An Intelligent Agent Based Intrusion Detection System Using Fuzzy Rough Set Based Outlier Detection. In: Patnaik, S., Yang, YM. (eds) Soft Computing Techniques in Vision Science. Studies in Computational Intelligence, vol 395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25507-6_13

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  • DOI: https://doi.org/10.1007/978-3-642-25507-6_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25506-9

  • Online ISBN: 978-3-642-25507-6

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