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Bang Wu

2 accepted papers

2026

Imprint of the Forgotten: Stealthy Membership Inference in Unlearned Graph Neural Networks

AAAI 2026technical

Graphs effectively model interactions in real-world applications such as social and trade networks, where Graph Neural Networks (GNNs) excel at tasks such as link prediction to enhance user experiences. Despite these benefits, users raise privacy concerns as user data can be exploited to improve GNN

Cited by 0SourcePDFScholar
2023

Demystifying Uneven Vulnerability of Link Stealing Attacks against Graph Neural Networks

ICML 2023poster

While graph neural networks (GNNs) dominate the state-of-the-art for exploring graphs in real-world applications, they have been shown to be vulnerable to a growing number of privacy attacks. For instance, link stealing is a well-known membership inference attack (MIA) on edges that infers the prese…

Cited by 26SourcePDFScholar