Combining Thermal Maps With Inception Neural Networks for Hardware Trojan Detection

Abstract

Hardware Trojan detection on modern integrated circuits (ICs) is a challenging task since the inspector may have no idea about the location and size of the embedded Trojan circuit. To achieve an accurate Trojan detection, instead of relying on hardware reverse engineering, a nondestructive technique based on thermal maps and inception neural networks (INNs) is proposed in this letter. The thermal maps generated by a Trojan-free (TF) IC chip and multiple emulated Trojan-infected (TI) IC chips are collected and optimized as the critical side-channel leakages at first. Then, INNs are utilized to analyze these optimized thermal maps to exactly extract the information of the embedded Trojans under the assistance of customized filters. As shown in the results, after training the INNs with 150 000 thermal maps, the corresponding Trojan detection accuracy can be achieved over 98.2%.