Hardware Trojan Detection

Hardware Trojan (HT) detection aims to identify malicious modifications secretly embedded in integrated circuits (ICs), a critical security concern in the outsourced manufacturing landscape. Current research focuses on developing advanced detection methods using machine learning, particularly deep learning architectures like graph convolutional networks and generative adversarial networks, often incorporating techniques like reinforcement learning for adaptive testing and contrastive learning for improved accuracy. These efforts are driven by the need for more effective, explainable, and scalable solutions that address limitations of existing methods, ultimately enhancing the security and trustworthiness of modern electronics.