Enhancing intrusion detection in wireless networks using radio frequency fingerprinting.

Abstract

Media access control (MAC) address spoofing can result in the unauthorized use of network resources. This paper demonstrates a novel approach, which incorporates radio frequency fingerprinting (RFF) into a wireless intrusion detection system (IDS), for detecting this attack. RFF is a technique that is used to uniquely identify a transceiver based on the transient portion of the signal it generates. Moreover, the success rate of a wireless IDS is also improved by correlating several observations in time, using a Bayesian filter. Simulation results, with an average success rate of (94-100%), support the feasibility of employing RFF and Bayesian filtering techniques to successfully address the aforementioned problem.