Parallelizing SAT-based de-camouflaging attacks by circuit partitioning and conflict avoiding

As one of the most effective proactive countermeasures against reverse engineering, circuit camouflaging has emerged to be a hot research topic and it is becoming a mature technology with the development of various de-camouflaging attacks. Among them, the SAT-based method is the most powerful one to defeat circuit camouflaging. However, SAT-based attacks have scalability problem due to the complexity of the underlying SAT solvers, and straightforward approach to parallelize SAT-based attacks will fail. In this article, we propose a novel parallelization framework for SAT-based attacks, which consists of a two-level partition method (independent module partitioning and k-medoids clustering), together with a novel conflict avoidance strategy. Specifically, we first break down the camouflaged netlist into multiple independent modules that can be solved in parallel. However, any good circuit camouflaging approach should produce one or multiple large modules. To solve this problem, we further apply the k-medoids algorithm to partition the large modules into multiple “high cohesion” and “low coupling” clusters. Utilizing the relative independence of these clusters, we propose a two-stage attack method to avoid conflicts among clusters. Experimental results on OpenSparc T1 microprocessor controller demonstrate that our approach can on average reduce the scales of the SAT formulas by more than 50%, reduce the attack iteration number by 45%, and achieves on average 3.6× and maximum 10× speed up over the best-known SAT-based de-camouflaging tool.