Efficient Trojan Detection via Calibration of Process Variations

In this paper we present an efficient method to detect hardware Trojans under high levels of process variations, by measuring delays for vectors generated using a minimally delay-invasive Trojan model. Our method focuses on various sources of process variations and significantly reduces the effects of variations on delays by calibrating delays measured on each fabricated chip. Using test structures and additional measurements on these, our approach significantly reduces the number of chips that we need to test to detect minimally-invasive Trojans with a desired level of confidence. Our approach for tackling high levels of process variations can be used in conjunction with any other type of parametric Trojan detection strategy to significantly improve its efficiency.