Topology-Aware Node Injection Attacks against graph neural networks
L Su, J Wang, Z Gan - Neurocomputing, 2025 - Elsevier
Graph neural networks (GNNs) are widely applied in real-life scenarios due to their excellent
performance in processing graph data. Meanwhile, GNNs are vulnerable to the node …
performance in processing graph data. Meanwhile, GNNs are vulnerable to the node …
Poster: AuditVotes: A Framework towards Deployable Certified Robustness for GNNs
Graph Neural Networks (GNNs) are powerful but vulnerable to adversarial attacks,
necessitating the research on certified robustness that can provide GNNs with robustness …
necessitating the research on certified robustness that can provide GNNs with robustness …
[PDF][PDF] AuditVotes: a Framework towards Deployable Certified Robustness for GNNs
Y Lai, K Zhou - comp.polyu.edu.hk
Graph Neural Networks (GNNs) are powerful but vulnerable to adversarial attacks,
necessitating the research on certified robustness that can provide GNNs with robustness …
necessitating the research on certified robustness that can provide GNNs with robustness …