HLIFT: A high-level information flow tracking method for detecting hardware Trojans
Chenguang Wang, Yici Cai, Qiang Zhou · 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC) · 2018
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. To solve this problem, we propose a feature matching method based on information flow tracking at high abstraction level. 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.