A Hardware Trojan Insertion Framework against Gate-Level Netlist Structural Feature-based and SCOAP-based Detection

The division of labor in the integrated circuit (IC) industry has become more detailed. Outsourcing IC design or fabrication to third-party vendors is inevitable, which has caused a variety of hardware security issues. With the attention of hardware Trojan, most recent research has focused on detection techniques instead of attack or insertion methods. Existing detection methods for gate level can be classified into two categories: one based on circuit structure features and the other based on the Sandia Controllability/Observability Analysis Program (SCOAP) values. This paper proposes a new hardware Trojan insertion framework that can automatically construct Trojan with low SCOAP values against both structural features-based and SCOAP-based detection techniques. In our framework, we use the greedy algorithm to build a Trojan structure similar to a genuine circuit as much as possible and then reduce SCOAP values by inserting genuine nets. The experimental results demonstrated that our greedy method achieves significant improvements in structure generation than the random method. Moreover, the insertion framework can reduce the average SCOAP values by 68% after inserting three genuine nets. Finally, we evaluate state-of-the-art detection techniques using hardware Trojan samples generated by our proposed framework, which provides a high False Positive Rate (FPR)/False Negative Rate (FNR) and low accuracy.