論文ID: 16.20181065
Side channel based hardware Trojan detection is one of the most investigated schemes to ensure the trustworthiness of integrated circuits (ICs). However, nearly all of the side-channel methods require a golden chip reference, either a trusted fabricated circuit or layout, which is very difficult to access in reality. In this paper, we propose a golden chip free electromagnetic (EM) side channel simulation and statistical Trojan detection framework. We utilize the design data at early stage of the IC lifecycle to generate EM radiation, and the generated EM traces serve as the golden reference. In order to leverage the EM signatures, a neural network algorithm is utilized for Trojan detection. Experimental results on selected AES benchmarks on FPGA show that the proposed method can effectively detect Trojans with the presence of noise and variations.
