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HyperAttack: Multi-Gradient-Guided White-box Adversarial Structure Attack of Hypergraph Neural Networks. (arXiv:2302.12407v1 [cs.LG])
cs.CR updates on arXiv.org arxiv.org
Hypergraph neural networks (HGNN) have shown superior performance in various
deep learning tasks, leveraging the high-order representation ability to
formulate complex correlations among data by connecting two or more nodes
through hyperedge modeling. Despite the well-studied adversarial attacks on
Graph Neural Networks (GNN), there is few study on adversarial attacks against
HGNN, which leads to a threat to the safety of HGNN applications. In this
paper, we introduce HyperAttack, the first white-box adversarial attack
framework against hypergraph neural networks. HyperAttack …
adversarial adversarial attacks applications attack attacks box data deep learning high modeling networks neural networks nodes order performance representation safety study threat