An R-SIFT Image Matching Intelligent Algorithm Applied to Hardware Trojan Detection
Chen Sun, Pujiang Liang, Lingling Li, Jingjing Ma, Licheng Jiao, Fang Liu · Journal of Physics Conference Series · 2021
Abstract Malicious modification, deletion or addition of some modules in the integrated circuits (ICs) will cause the chip to be attacked, which is called Hardware Trojans (HTs). Reverse engineering (RE) is a classic destructive method and widely used in HTs detection. However, RE is very time-consuming and error prone. In this paper, based on RE, we propose the R-SIFT algorithm to match image and reformulate the Trojan detection problem as change detection problem. For the R-SIFT algorithm, the ratio of exponentially weighted averages (Roewa) operator is introduced into the scale-invariant feature transform (SIFT) algorithm. Experiments show that the proposed method has 7 to 56 times more matching points than the original SIFT can be effectively applied to HTs detection.