Enhancing the SVDD accuracy in Intrusion Detection Systems by removing external voids

Kenaza, Tayeb and Bennaceur, Khadidja and Labed, Abennour and Aiash, Mahdi (2016) Enhancing the SVDD accuracy in Intrusion Detection Systems by removing external voids. In: 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-16), 23-25 Aug 2016, Tianjin, China.

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Abstract

This work aims to improve the accuracy of the SVDD-based Intrusion Detection Systems. In this study we are interested by approaches using only one-class classification, namely the class of normal user sessions. Sessions are modeled by vectors of points in a finite features space. The goal of using the SVDD in anomaly detection is to find the hypersphere with a minimal volume that encloses the entire scatter of points (i.e. the normal sessions). This paper discusses the general case where the shape of the scatter is arbitrary. In this case some voids can occur between the scatter and the boundary of the hypersphere, and mainly cause a distortion of the data description that reduces the accuracy of the detection. The objective of this work is to study and highlight the best techniques that help removing voids and thus improving the accuracy of the SVDD. Experimental results show that choosing the appropriate techniques and parameters can significantly improve the accuracy of the SVDD.

Item Type: Conference or Workshop Item (Paper)
Additional Information: T. Kenaza, K. Bennaceur, A. Labed and M. Aiash, "Enhancing the SVDD Accuracy in Intrusion Detection Systems by Removing External Voids," 2016 IEEE Trustcom/BigDataSE/ISPA, Tianjin, 2016, pp. 1765-1770. doi: 10.1109/TrustCom.2016.0271
Research Areas: A. > School of Science and Technology > Computer and Communications Engineering
Item ID: 21924
Notes on copyright: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Depositing User: Mahdi Aiash
Date Deposited: 07 Jun 2017 13:56
Last Modified: 11 Sep 2018 05:04
URI: http://eprints.mdx.ac.uk/id/eprint/21924

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