Unauthorized Bluetooth devices or rogue devices can impersonate legitimate devices through address and link key spoofing. Moreover, they can infiltrate a Bluetooth network and initiate other forms of attacks. This paper investigates a novel intrusion detection approach, which makes use of radio frequency fingerprinting (RFF) for profiling, Hotelling's T2 statistics for classification and a decision filter, for detecting these devices. RFF is a technique that is used to uniquely identify a transceiver based on the transient portion of the signal it generates. Moreover, the use of a statistical classifier proves advantageous in minimizing requirements for memory. Finally, the detection rate is also improved by incorporating a decision filter, which takes the classification results of a set of events into consideration, prior to rendering the final decision. The average False Alarm Rate of five percent and Detection Rate of ninety-three percent support the feasibility of employing these components to address the aforementioned problem.

Additional Metadata
Keywords Bluetooth rogue devices, Hotelling's T2 statistics, Intrusion detection, Network security, Radio frequency fingerprinting, Wireless networks
Conference 3rd IASTED International Conference on Communications and Computer Networks, CCN 2006
Citation
Hall, J. (Jeyanthi), Barbeau, M, & Kranakis, E. (2006). Detecting rogue devices in bluetooth networks using radio frequency fingerprinting. Presented at the 3rd IASTED International Conference on Communications and Computer Networks, CCN 2006.