Hardware Trojan Detection Utilizing Machine Learning Approaches
Kento Hasegawa, Youhua Shi, Nozomu Togawa · 2018
Hardware security has become a serious concern in recent years. Due to the outsourcing in hardware production, malicious circuits (or hardware Trojans) can be easily inserted into hardware products by attackers. Since hardware Trojans are tiny and stealthy, their detection is difficult. Under the circumstances, numerous hardware-Trojan detection methods have been proposed. In this paper, we elaborate the overview of hardware-Trojan detection and review the hardware-Trojan detection methods using machine learning which is one of the state-of-the-art approaches.