  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.
