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Deep learning based RF fingerprinting for device identification and wireless security

Deep learning based RF fingerprinting for device identification and wireless security

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RF fingerprinting is an emerging technology for identifying hardware-specific features of wireless transmitters and may find important applications in wireless security. In this study, the authors present a new RF fingerprinting scheme using deep neural networks. In particular, a long short-term memory based recurrent neural network is proposed and used for automatically identifying hardware-specific features and classifying transmitters. Experimental studies using identical RF transmitters showed very high detection accuracy in the presence of strong noise (signal-to-noise ratio as low as dB) and demonstrated the effectiveness of the proposed scheme.

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