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Autores principales: Rušiņš, Artis, Nesenbergs, Krišjānis, Tiščenko, Deniss, Paikens, Pēteris
Formato: Preprint
Publicado: 2024
Materias:
Acceso en línea:https://arxiv.org/abs/2402.06250
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author Rušiņš, Artis
Nesenbergs, Krišjānis
Tiščenko, Deniss
Paikens, Pēteris
author_facet Rušiņš, Artis
Nesenbergs, Krišjānis
Tiščenko, Deniss
Paikens, Pēteris
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2402_06250
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An experimental study: RF Fingerprinting of Bluetooth devices
Rušiņš, Artis
Nesenbergs, Krišjānis
Tiščenko, Deniss
Paikens, Pēteris
Signal Processing
Networking and Internet Architecture
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.
title An experimental study: RF Fingerprinting of Bluetooth devices
topic Signal Processing
Networking and Internet Architecture
url https://arxiv.org/abs/2402.06250