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Detecting misbehaviour in WiFi using multi-layer metric data fusion

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conference contribution
posted on 14.02.2014 by Kostas Kyriakopoulos, Francisco Aparicio-Navarro, David Parish
One of the main problems in open wireless networks is the inability of authenticating the identity of a wireless client or Access Point (AP). This issue is a concern because, a malicious entity could masquerade as the legal AP and entice a wireless client to establish a connection with a Rogue AP. Previous work by the authors has developed the algorithms used in this work but, in contrast to prior work, there was no analysis or experimentation with Rogue AP attacks. Our purpose in this work is to detect injection type of Rogue AP activity by identifying whether a frame is genuinely transmitted by the legal AP or not. To this end, an identity profile for the legal AP is built by fusing multi-layer metrics, using the Dempster-Shafer algorithm. The results show high detection results with low false alarms for detecting Rogue AP attacks without requiring configuration from an administrator. © 2013 IEEE.

Funding

This work has been funded by the Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/H005005/1 ].

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

KYRIAKOPOULOS, K.G., APARICIO-NAVARRO, F.J. and PARISH, D.J., 2013. Detecting misbehaviour in WiFi using multi-layer metric data fusion. IN: Proceedings of the IEEE International Workshop on Measurements and Networking, Naples, Italy, 7-8 October 2013, pp. 155 - 160.

Publisher

© IEEE

Version

AM (Accepted Manuscript)

Publication date

2013

Notes

© 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.

ISBN

978-1-4673-2873-9

Language

en

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