2024/11/10 by Gabriele Oligeri, Savio Sciancalepore, Oligeri, Gabriele +1
Computer Science · #Biometric Identification and Security #Cryptography and Security (cs.CR) #Digital Media Forensic Detection #FOS: Computer and information sciences #Speech and Audio Processing
paper · pdf · doi:10.48550/arxiv.2411.06417
openalex publication_date 2024/11/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Radio Frequency Fingerprinting (RFF) techniques allow a receiver to authenticate a transmitter by analyzing the physical layer of the radio spectrum. Although the vast majority of scientific contributions focus on improving the performance of RFF considering different parameters and scenarios, in this work, we consider RFF as an attack vector to identify a target device in the radio spectrum. We propose, implement, and evaluate \em HidePrint, a solution to prevent identification through RFF without affecting the quality of the communication link between the transmitter and the receiver. \em HidePrint hides the transmitter's fingerprint against an illegitimate eavesdropper through the injection of controlled noise into the transmitted signal. We evaluate our solution against various state-of-the-art RFF techniques, considering several adversarial models, data from real-world communication links (wired and wireless), and protocol configurations. Our results show that the injection of a Gaussian noise pattern with a normalized standard deviation of (at least) 0.02 prevents device fingerprinting in all the considered scenarios, while affecting the Signal-to-Noise Ratio (SNR) of the received signal by only 0.1 dB. Moreover, we introduce \em selective radio fingerprint disclosure, a new technique that allows the transmitter to disclose the radio fingerprint to only a subset of intended receivers.