Date of Award

11-20-2008

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Raheem A Beyah - Chair

Second Advisor

Anu Bourgeois

Third Advisor

Xiaojun Cao

Abstract

We propose a simple, passive and deployable approach for fingerprinting traffic on the wired side as a solution for three critical stealth attacks in wireless networks. We focus on extracting traces of the 802.11 medium access control (MAC) protocol from the temporal arrival patterns of incoming traffic streams as seen on the wired side, to identify attacker behavior. Attacks addressed include unauthorized access points, selfish behavior at the MAC layer and MAC layer covert timing channels. We employ the Bayesian binning technique as a means of classifying between delay distributions. The scheme requires no change to the 802.11 nodes or protocol, exhibits minimal computational overhead and offers a single point of discovery. We evaluate our model using experiments and simulations.

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