AttackGNN: Red-Teaming GNNs in Hardware Security Using Reinforcement Learning

arXiv:2402.13946v1 Announce Type: cross
Abstract: Machine learning has shown great promise in addressing several critical hardware security problems. In particular, researchers have developed novel graph neural network (GNN)-based techniques for detecting intellectual property (IP) piracy, detecting hardware Trojans (HTs), and reverse engineering circuits, to name a few. These techniques have demonstrated outstanding accuracy and have received much attention in the community. However, since these techniques are used for security applications, it is imperative to evaluate them thoroughly and ensure they …

arxiv critical cs.cr cs.lg engineering graph great hardware hardware security hts intellectual property machine machine learning name network neural network novel piracy problems property researchers reverse reverse engineering security techniques trojans