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

arXiv:2402.13946v1 Announce Type: new
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 …

abstract arxiv cs.cr cs.lg engineering gnn gnns graph graph neural network hardware intellectual property machine machine learning network neural network novel property reinforcement reinforcement learning researchers security type