52 citations · 529 across the 30 of their papers we have counts for
4 papers · 1 filter
Reinforcement Learning for Hardware Security: Opportunities, Developments, and Challenges
Satwik Patnaik, Vasudev Gohil, Hao Guo +2
Reinforcement learning (RL) is a machine learning paradigm where an autonomous agent learns to make an optimal sequence of decisions by interacting with the underlying environment.…
ATTRITION: Attacking Static Hardware Trojan Detection Techniques Using Reinforcement Learning
Vasudev Gohil, Hao Guo, Satwik Patnaik +2
Stealthy hardware Trojans (HTs) inserted during the fabrication of integrated circuits can bypass the security of critical infrastructures. Although researchers have proposed many…
DETERRENT: Detecting Trojans using Reinforcement Learning
Vasudev Gohil, Satwik Patnaik, Hao Guo +3
Insertion of hardware Trojans (HTs) in integrated circuits is a pernicious threat. Since HTs are activated under rare trigger conditions, detecting them using random logic simulati…
Embracing Graph Neural Networks for Hardware Security (Invited Paper)
Lilas Alrahis, Satwik Patnaik, Muhammad Shafique +1
Graph neural networks (GNNs) have attracted increasing attention due to their superior performance in deep learning on graph-structured data. GNNs have succeeded across various dom…