A Hard Label Black-box Adversarial Attack Against Graph Neural Networks
Jiaming Mu, Binghui Wang, Qi Lecky Li, Kun Sun, Mingwei Xu, Zhuotao Liu · 2021
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in various graph structure related tasks such as node classification and graph classification. However, GNNs are vulnerable to adversarial attacks. Existing works mainly focus on attacking GNNs for node classification; nevertheless, the attacks against GNNs for graph classification have not been well explored.