Implementing Region-Based Segmentation for Hardware Trojan Detection in FPGAs Cell-Level Netlist

Abstract

Field Programmable Gate Array (FPGA) is gaining popularity because of their reconfigurability which brings in security concerns like inserting hardware trojan. Various detection methods to overcome this threat have been proposed but in the ASIC's supply chain and cannot directly apply to the FPGA application. In this paper, the authors aim to implement a structural feature-based detection method for detecting hardware trojan in a cell-level netlist, which is not well explored yet, where the nets are segmented into smaller groups based on their interconnection and further analyzed by looking at their structural similarities. Experiments show positive performance with an average detection rate of 95.41%, an average false alarm rate of 2.87% and average accuracy of 96.27%.