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An experimental study: RF Fingerprinting of Bluetooth devices

Published: 15 December 2023 Publication History

Abstract

This paper presents an experimental study on radio frequency (RF) fingerprinting of Bluetooth Classic devices. Our research aims to provide a practical evaluation of the possibilities for RF fingerprinting of everyday Bluetooth connected devices that may cause privacy risks. We have built an experimental setup for recording Bluetooth connection in a radio frequency isolated environment using commercially available SDR (software defined radio) systems, extracted fingerprints of the Bluetooth radio data in the form of carrier frequency offset and scaling factor from 6 different devices, and performed k-nearest neighbors (kNN) classification achieving 84% accuracy. The experiment demonstrates that no matter what privacy measures are being taken in the protocol layer, the physical layer leaks significant information about the device to unauthorized listeners. In the context of the ever-growing Bluetooth device market, this research serves as a clarion call for device manufacturers, regulators, and end-users to acknowledge the privacy risks posed by RF fingerprinting and lays a foundation for more sizeable Bluetooth fingerprinting analysis research.

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EWSN '23: Proceedings of the 2023 International Conference on embedded Wireless Systems and Networks
December 2023
426 pages

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Association for Computing Machinery

New York, NY, United States

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Published: 15 December 2023

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September 25 - 27, 2023
Rende, Italy

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EWSN '23 Paper Acceptance Rate 31 of 56 submissions, 55%;
Overall Acceptance Rate 81 of 195 submissions, 42%

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