DevFing: Robust LCR Based Device Fingerprinting

Abstract

Ahstract- The continuous growth of IoT technologies raises several security concerns and challenges. Device identification and authentication are the key challenges due to the significant presence of malicious/counterfeited devices. The traditional approaches used to identify counterfeited devices, e.g., digital signatures, hardware watermarking, or techniques based on IPV4/IPV6, fail to be directly applied to the resource-constrained IoT end-nodes. The advancement in sophisticated counterfeiter tools and technologies makes these problems even more daunting. In this direction, we propose DevFing - A Device Fingerprinting approach based on Hardware Intrinsic Security (HIS) mechanism. DevFing employs an electronic board s intrinsic characteristics such that Inductance (L), Capacitance (C), Resistance (R), and Impedance (Z) to identify each device uniquely. We propose a dedicated daughterboard design to measure and generate robust device fingerprints from these intrinsic properties. The board s error- correcting module enhances the robustness by utilizing a fuzzy extractor for error mitigation and regeneration. We have carried out extensive experiments and simulations on the embedded system boards (Raspberry Pi-3B) and desktop to validate DevFing. Our approach improved the fingerprint matching accuracy for the 64 bits key from 44.2% to 100% with a fuzzy extractor/error- correctina module with the hamming distance of 5.