Hardware Trojan Detection Based on Signal Correlation
Wei Zhao, Haihua Shen, Huawei Li, Xiaowei Li · 2018
Hardware Trojan has attracted more and more attention from academia and industry because of its significant potential threat. Long activation time is a major concern during Trojan detection process. Traditional pre-silicon verification and post-silicon testing cannot be extended to detect hardware Trojans efficiently because Trojan is usually activated under specific rare conditions. In this paper, we propose a novel approach to expose Trojans efficiently by increasing the transition activities of ASIC logic regions hard to reach. Specifically, the proposed approach detects the "local" regions with low reachability by calculating signals statistical correlation, and detect the "local" regions with low reachability. In addition, by analyzing the global correlations between primary inputs and these rare regions, a retrospective test stimulus generation algorithm is developed to better control the internal logic alteration. Besides, we propose an output sequence model based on CRC check. The experiment results show that the Trojan activation time can be significantly decreased and the Trojans being exposed can be increased dramatically with the proposed method.