Hyeon Park1, SeoYeon Kim2, Seok Min Ko1, TaeGuen Kim2,*
CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1891-1909, 2023, DOI:10.32604/cmc.2023.039464
- 30 August 2023
Abstract The rapid growth of modern vehicles with advanced technologies requires strong security to ensure customer safety. One key system that needs protection is the passive key entry system (PKES). To prevent attacks aimed at defeating the PKES, we propose a novel radio frequency (RF) fingerprinting method. Our method extracts the cepstral coefficient feature as a fingerprint of a radio frequency signal. This feature is then analyzed using a convolutional neural network (CNN) for device identification. In evaluation, we conducted experiments to determine the effectiveness of different cepstral coefficient features and the convolutional neural network-based model. More >
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