Hausdorff Distance Model-Based Identity Authentication for IP Circuits in Service-Centric Internet-of-Things Environment

Abstract

Rapid advances in the Internet-of-Things (IoT) have exposed the underlying hardware devices to security threats. As the major component of hardware devices, the integrated circuit (IC) chip also suffers the threat of illegal, malicious attacks. To protect against attacks and vulnerabilities of a chip, a credible authentication is of fundamental importance. In this paper, we propose a Hausdorff distance-based method to authenticate the identity of IC chips in IoT environments, where the structure is analyzed, and the lookup table (LUT) resources are treated as a set of reconfigurable nodes in field programmable gate array (FPGA)-based IC design. Unused LUT resources are selected for insertion of the copyright information by using the depth-first search algorithm, and the random positions are reordered with the Hausdorff distance matching function next, so these positions are mapped to satisfy the specific constraints of the optimal watermark positions. If the authentication process is activated, virtual positions are mapped to the initial key file, yet the identity of the IC designed can be authenticated using the mapping relationship of the Hausdorff distance function. Experimental results show that the proposed method achieves good randomness and secrecy in watermark embedding, as well the extra resource overhead caused by watermarks are promising.