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Graph Neural Networks for Hardware Vulnerability Analysis -- Can you Trust your GNN?. (arXiv:2303.16690v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
The participation of third-party entities in the globalized semiconductor
supply chain introduces potential security vulnerabilities, such as
intellectual property piracy and hardware Trojan (HT) insertion. Graph neural
networks (GNNs) have been employed to address various hardware security
threats, owing to their superior performance on graph-structured data, such as
circuits. However, GNNs are also susceptible to attacks. This work examines the
use of GNNs for detecting hardware threats like HTs and their vulnerability to
attacks. We present BadGNN, a backdoor attack …
address analysis attack attacks backdoor data entities hardware hardware security hardware vulnerability hide hts intellectual property networks neural networks participation party performance piracy security security threats semiconductor structured data supply supply chain third third-party threats trojan trust vulnerabilities vulnerability vulnerability analysis work