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Manual and automatic assigned thresholds in multi-layer data fusion intrusion detection system for 802.11 attacks

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journal contribution
posted on 06.02.2014, 16:09 by Kostas Kyriakopoulos, Francisco Aparicio-Navarro, David Parish
Abuse attacks on wireless networks are becoming increasingly sophisticated. Most of the recent research on intrusion detection systems for wireless attacks either focuses on just one layer of observation or uses a limited number of metrics without proper data fusion techniques. However, the true status of a network is rarely accurately detectable by examining only one network layer. The goal of this study is to detect injection types of attacks in wireless networks by fusing multi-metrics using the Dempster–Shafer (D–S) belief theory. When combining beliefs, an important step to consider is the automatic and selfadaptive process of basic probability assignment (BPA). This study presents a comparison between manual and automatic BPA methods using the D–S technique. Custom tailoring BPAs in an optimum manner under specific network conditions could be extremely time consuming and difficult. In contrast, automatic methods have the advantage of not requiring any prior training or calibration from an administrator. The results show that multi-layer techniques perform more efficiently when compared with conventional methods. In addition, the automatic assignment of beliefs makes the use of such a system easier to deploy while providing a similar performance to that of a manual system.

Funding

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/H005005/1 ]

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IET Information Security

Volume

8

Issue

1

Pages

42 - 50

Citation

KYRIAKOPOULOS, K.G., APARICIO-NAVARRO, F.J. and PARISH, D.J., 2014. Manual and automatic assigned thresholds in multi-layer data fusion intrusion detection system for 802.11 attacks. IET Information Security, 8 (1), pp. 42 - 50.

Publisher

© The Institution of Engineering and Technology

Version

AM (Accepted Manuscript)

Acceptance date

11/02/2013

Publication date

2014-01-01

Copyright date

2014

Notes

This paper was published in the journal, IET Information Security [© The Institution of Engineering and Technology] and the definitive version is available at: http://dx.doi.org/10.1049/iet-ifs.2012.0302

ISSN

1751-8709

eISSN

1751-8717

Language

en

Exports