1 citations · 2 across the 6 of their papers we have counts for
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BadGraph: A Backdoor Attack Against Latent Diffusion Model for Text-Guided Graph Generation
Liang Ye, Shengqin Chen, Jiazhu Dai
The rapid progress of graph generation has raised new security concerns, particularly regarding backdoor vulnerabilities. Though prior work has explored backdoor attacks against di…
Graph-Level Label-Only Membership Inference Attack against Graph Neural Networks
Jiazhu Dai, Yubing Lu
Graph neural networks (GNNs) are widely used for graph-structured data but are vulnerable to membership inference attacks (MIAs) in graph classification tasks, which determine if a…
A Semantic and Clean-label Backdoor Attack against Graph Convolutional Networks
Jiazhu Dai, Haoyu Sun
Graph Convolutional Networks (GCNs) have shown excellent performance in graph-structured tasks such as node classification and graph classification. However, recent research has sh…
Effective backdoor attack on graph neural networks in link prediction tasks
Jiazhu Dai, Haoyu Sun
Graph Neural Networks (GNNs) are a class of deep learning models capable of processing graph-structured data, and they have demonstrated significant performance in a variety of rea…