Injecting Reliable Radio Frequency Fingerprints Using Metasurface for The Internet of Things

June 12, 2020 Β· Declared Dead Β· πŸ› IEEE Transactions on Information Forensics and Security

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Authors Sekhar Rajendran, Zhi Sun, Feng Lin, Kui Ren arXiv ID 2006.06895 Category eess.SP: Signal Processing Cross-listed cs.CR, eess.SY Citations 53 Venue IEEE Transactions on Information Forensics and Security Last Checked 5 months ago
Abstract
In Internet of Things, where billions of devices with limited resources are communicating with each other, security has become a major stumbling block affecting the progress of this technology. Existing authentication schemes-based on digital signatures have overhead costs associated with them in terms of computation time, battery power, bandwidth, memory, and related hardware costs. Radio frequency fingerprint (RFF), utilizing the unique device-based information, can be a promising solution for IoT. However, traditional RFFs have become obsolete because of low reliability and reduced user capability. Our proposed solution, Metasurface RF-Fingerprinting Injection (MeRFFI), is to inject a carefully-designed radio frequency fingerprint into the wireless physical layer that can increase the security of a stationary IoT device with minimal overhead. The injection of fingerprint is implemented using a low cost metasurface developed and fabricated in our lab, which is designed to make small but detectable perturbations in the specific frequency band in which the IoT devices are communicating. We have conducted comprehensive system evaluations including distance, orientation, multiple channels where the feasibility, effectiveness, and reliability of these fingerprints are validated. The proposed MeRFFI system can be easily integrated into the existing authentication schemes. The security vulnerabilities are analyzed for some of the most threatening wireless physical layer-based attacks.
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