Fusing Multi-Layer Metrics for Detecting Security Attacks in 802.11 Networks.pdf (645.2 kB)
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Fusing multi-layer metrics for detecting security attacks in 802.11 networks

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conference contribution
posted on 06.05.2011 by Kostas Kyriakopoulos, Francisco Aparicio-Navarro, David Parish
Computer networks and more specifically wireless communication networks are increasingly becoming susceptible to more sophisticated and untraceable attacks. Most of the current Intrusion Detection Systems either focus on just one layer of observation or use 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 or metric. Ideally, a synergistic approach would require knowledge from various layers to be fused and, collectively, an ultimate decision to be taken. To this aim, the Dempster-Shafer (D-S) approach is examined as a data fusion algorithm that combines beliefs of multiple metrics across multiple layers. This paper describes the methodology of using metrics from multiple layers of wireless communication networks for detecting wireless security breaches. The metrics are analysed and compared to historical data and each gives a belief of whether an attack takes place or not. The beliefs from different metrics are fused with the D-S technique with the ultimate goal of limiting false alarms by combining beliefs from various network layers. The results show that cross-layer techniques and data fusion perform more efficiently in a variety of situations compared to conventional methods.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

KYRIAKOPOULOS, K.G., APARICIO-NAVARRO, F.J. and PARISH, D.J., 2011. Fusing multi-layer metrics for detecting security attacks in 802.11 networks. IN: Proceeedings of WTS 2011. Wireless Telecommunications Symposium, New York, USA, 13th-15th April.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2011

Notes

This is a conference paper. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISBN

9781457701610

Language

en

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