A high-level information flow tracking method for detecting information leakage
Haoyi Wang, Chenguang Wang, Yici Cai, Qiang Zhou · Integration · 2019
In this paper, we note that the hardware Trojans that leak information through the unspecified output pins are difficult to detect by functional testing or side-channel signal analysis. Especially, the Trojans that leak the information through the side channel has proven stealthy to be detected. To solve this problem, we propose a feature matching method based on information flow tracking at high abstraction level. In this paper, the Trojans features are summarized with the format of high-level information flow tracking, which can be used to detect the Trojans. Experimental results show that our method can successfully identify the above-mentioned Trojans from Trust-hub, DeTrust, and OpenCores in less than 20 ms, showing significantly lower time complexity compared with the existing works.