Delay based hardware Trojan detection exploiting spatial correlations to suppress variations

Abstract

Hardware Trojan detection is a crucial problem with many dimensions and high complexity. Side channel analysis based methods are advantageous for not requiring Trojan activation but deeply suffer from process variations, the inability to detect small Trojans as well as the requirement for golden chips. In this paper, a non-invasive, golden chip free delay based hardware Trojan detection method is proposed. It exploits the inherent spatial correlations to suppress the Trojan hiding effect of the variations. The method is verified using post-manufacturing simulations under an elaborative variation model considering both inter and intra die components. The results reveal that although delay-alone approach fails to detect minimal Trojans, the proposed method achieves the detection securing more than 91% percent of a circuit on average. Moreover, if the trigger detection in cooperation with the payload detection is utilized, the detection probability exceeds 99%.