Automated Detection of Hardware Trojans using Power Side-Channel Analysis and VGG-Net

With the expanding usage of electronic devices such as smartphones and smartwatches in daily life, the need for advanced Integrated Circuits (ICs) is also increasing. Corporations are compelled to outsource IC design and production to several third-party vendors to keep up with demand. This has allowed adversaries to make unauthorized modifications to the circuits. As a result, malicious adversaries have been able to deploy Hardware Trojans (HTs), similar to software viruses, as they may cause data leakage and circuit disruption. The currently known methods for HT detection rely on expensive and often impractical destructive methods like reverse engineering or non-destructive methods like comparison with the golden chip. In this paper, we propose a method for detecting HTs based on the VGG-Net architecture. The model has an accuracy of 93%, 87%, 100%, 100%, and 76% on the Advanced Encryption Standard (AES) benchmarks of T500, T600, T700, T800, and T1600, respectively, for an average accuracy of 91.2%. It surpasses existing state-of-the-art models in the AES-T600, AES-T700, AES-T800, and AES-T1600 benchmarks.