Attacks on Node Attributes in Graph Neural Networks

arXiv:2402.12426v2 Announce Type: replace-cross
Abstract: Graphs are commonly used to model complex networks prevalent in modern social media and literacy applications. Our research investigates the vulnerability of these graphs through the application of feature based adversarial attacks, focusing on both decision time attacks and poisoning attacks. In contrast to state of the art models like Net Attack and Meta Attack, which target node attributes and graph structure, our study specifically targets node attributes. For our analysis, we utilized the text …

adversarial adversarial attacks application applications arxiv attacks attributes cs.cr cs.lg cs.si decision feature graph graphs media networks neural networks node poisoning poisoning attacks prevalent research social social media state vulnerability