Temperature Tracking: Toward Robust Run-Time Detection of Hardware Trojans

Abstract

The hardware Trojan threat has motivated development of Trojan detection schemes at all stages of the integrated circuit (IC) lifecycle. While the majority of existing schemes focus on ICs at test-time, there are many unique advantages offered by post-deployment/run-time Trojan detection. However, run-time approaches have been underutilized with prior work highlighting the challenges of implementing them with limited hardware resources. In this paper, we propose three innovative low-overhead approaches for run-time Trojan detection which exploit the thermal sensors already available in many modern systems to detect deviations in power/thermal profiles caused by Trojan activation. The first one is a local sensor-based approach that uses information from thermal sensors together with hypothesis testing to make a decision. The second one is a global approach that exploits correlation between sensors and maintains track of the ICs thermal profile using a Kalman filter (KF). The third approach incorporates leakage power into the system dynamic model and apply extended KF (EKF) to track ICs thermal profile. Simulation results using state-of-the-art tools on ten publicly available Trojan benchmarks verify that all three proposed approaches can detect active Trojans quickly and with few false positives. Among three approaches, EKF is flawless in terms of the ten benchmarks tested but would require the most overhead.