[en] As the spectrum becomes increasingly crowded, quick and reliable authentication of wireless devices is critical to avoid harmful interference to incumbents of the spectrum. Radio fingerprinting achieves fast waveform-level authentication by distinguishing devices based on unique hardware imperfections in the radio circuitry. However, existing approaches can fingerprint only one signal in a specific band, making them inapplicable in real-world scenarios where multiple signals coexist in spectrum bands. This paper introduces Multi-band Multi-device Radio Fingerprinting (M2RF) to address this challenge. Specifically, we propose a learning-driven segmentation algorithm to directly process in-phase/quadrature (I/Q) samples coming from the receiver and assign each I/Q sample to a specific radio. In contrast to existing approaches, M2RF simultaneously identifies and locates in the spectrum multiple devices that emit overlapping signals and avoids the burden of processing data, making the overall approach with reduced overhead and faster. Our approach can be generalized to different channels and signal bandwidths without retraining, making it scalable. Experiments in three different spectrum scenarios under 2 transmission conditions and with 15 radio transmitters demonstrate the effectiveness of M2RF, achieving up to 99.56% of F1-score, and 92.44% detection rate of malicious users with only a 2.72% mean Miss Rate (MR). A demo video of M2RF is available (https://youtu.be/tc3EamlmOgQ).
Disciplines :
Computer science
Author, co-author :
ALLA, Ildi ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Systems and Network Security Group (SNS) ; Inria Lille-Nord Europe, France
Zhang, Milin; Institute for the Wireless Internet of Things at Northeastern University, United States
Ashdown, Jonathan; Air Force Research Laboratory, United States
Loscri, Valeria; Inria Lille-Nord Europe, France
Restuccia, Francesco; Institute for the Wireless Internet of Things at Northeastern University, United States
External co-authors :
yes
Language :
English
Title :
Finding a Needle in a (Spectrum) Haystack: Multi-Band Multi-Device Radio Fingerprinting
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