Novel Techniques for High-Sensitivity Hardware Trojan Detection Using Thermal and Power Maps

Hardware Trojans are malicious alterations or injections of unwanted circuitry to integrated circuits (ICs) by untrustworthy factories. They render great threat to the security of modern ICs by various unwanted activities such as bypassing or disabling the security fence of a system, leaking confidential information, deranging, or destroying the entire chip. Traditional testing strategies are becoming ineffective since these techniques suffer from decreased sensitivity toward small Trojans because of oversized chip and large amount of process variation present in nanometer technologies. The production volume along with decreased controllability and observability to complex ICs internals make it difficult to efficiently perform Trojan detection using typical structural tests like path latency and leakage power. In this paper, we propose a completely new post-silicon multimodal approach using runtime thermal and power maps for Trojan detection and localization. Utilizing the novel framework, we propose two different Trojan detection methods involving 2-D principal component analysis. First, supervised thresholding in case training data set is available and second, unsupervised clustering which require no prior characterization data of the chip. We introduce l(1) regularization in the thermal to power inversion procedure which improves Trojan detection accuracy. To characterize ICs accurately, we perform our experiments in presence of realistic CMOS process variation. Our experimental evaluations reveal that our proposed methodology can detect very small Trojans with 3-4 orders of magnitude smaller power consumptions than the total power usage of the chip, while it scales very well because of the spatial view to ICs internals by the thermal mapping.