Test Pattern generation for detection of Hardware Trojans based on improved Genetic Algorithm

Abstract

Hardware Trojans (HT) are minuscule circuits embedded by an adversary for malicious purposes. Such circuits posses stealthy nature and can cause disruption upon activation. To detect the presence of such circuits, appropriate test vectors need to be applied. In this regard, the genetic algorithm (GA) seems to be the most promising technique due to its exploration capability. However, like most of the existing techniques, GA also suffers from exploring the huge search space. In this article a GA based methodology is proposed incorporating the information about potential inputs into it. Experimental results analysis signifies that the identification of the relevant inputs for GA provides an optimal solution. The significance of proposed methodology is endorsed by applying the proposed GA technique on different ISCAS '85 benchmark circuits. A noteworthy improvement on run time is observed while simultaneously providing improved test set quality than the state-of-the art technique.