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A Database for the Radio Frequency Fingerprinting of Bluetooth Devices

1
Department of Avionics, Atilim University, 06830 Ankara, Turkey
2
Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, 2815 Gjøvik, Norway
3
Department of Electrical Electronics Engineering, Atilim University, 06830 Ankara, Turkey
*
Author to whom correspondence should be addressed.
Received: 19 May 2020 / Revised: 16 June 2020 / Accepted: 19 June 2020 / Published: 21 June 2020
(This article belongs to the Special Issue Data from Smartphone and Wearables)
Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) transmitted from wireless devices in order to classify authorized users. The most important requirement to develop an RFF method is the existence of a precise, robust, and extensive database of the emitted signals. In this context, this paper introduces a database consisting of Bluetooth (BT) signals collected at different sampling rates from 27 different smartphones (six manufacturers with several models for each). Firstly, the data acquisition system to create the database is described in detail. Then, the two well-known methods based on transient BT signals are experimentally tested by using the provided data to check their solidity. The results show that the created database may be useful for many researchers working on the development of the RFF of BT devices. View Full-Text
Keywords: Bluetooth; classification; data acquisition; emitter identification; radio frequency fingerprinting; RF front end Bluetooth; classification; data acquisition; emitter identification; radio frequency fingerprinting; RF front end
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MDPI and ACS Style

Uzundurukan, E.; Dalveren, Y.; Kara, A. A Database for the Radio Frequency Fingerprinting of Bluetooth Devices. Data 2020, 5, 55.

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