DGHSA: derivative graph-based hypergraph structure attack
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DOI: 10.1038/s41598-024-79824-y
Abstract: Hypergraph Neural Networks (HGNNs) have been significantly successful in higher-order tasks. However, recent study have shown that they are also vulnerable to adversarial attacks like Graph Neural Networks. Attackers fool HGNNs by modifying node links… read more here.
Keywords: attack; based hypergraph; derivative graph; hypergraph ... See more keywords