Multi-criteria Hardware Trojan Detection: A Reinforcement Learning Approach

Understand

Hardware Trojans (HTs) are undesired design or manufacturing modifications that can severely alter the security and functionality of digital integrated circuits.

• HTs can be inserted according to various design criteria, e.g., nets switching activity, observability, controllability, etc.
• However, to our knowledge, most HT detection methods are only based on a single criterion, i.e., nets switching activity.
• This paper proposes a multi-criteria reinforcement learning (RL) HT detection tool that features a tunable reward function for different HT detection scenarios.