Monte Carlo Based Test Pattern Generation for Hardware Trojan Detection

Hardware Trojan (HT) has emerged as a serious security threat to many critical systems. HT detection techniques are badly needed to ensure trust in hardware systems. In related works, only a fixed large number of random patterns are applied, with no regard to the pattern´s effect to HT detection result. The variations in target signal caused by different sets of input vectors are not addressed. There is also no guarantee that the vector set used is long enough to be representative or whether it is already over testing. To solve these problems, we propose a Monte Carlo based test pattern generation method for HT detection. The proposed approach offers a solution by sampling the detection until the standard deviation of the measured signal over all the samples is within certain accuracy. This gives us the confidence in the signal measurement without having to do exhaustive test. Moreover, it is conducive to simplify test vector sets. Experiment results on ISCAS89 benchmarks showed that the proposed approach usually needs much less time than that required by exhaustive test to achieve reliable results and desired accuracy.