An empirical study showing that graph prompt learning exposes node attributes and links to inference attacks, with prompt tuning adding little extra risk over frozen GNN baselines.
Local differential private spatio- temporal dynamic graph learning for wireless social networks,
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GraphTheft: Quantifying Privacy Risks in Graph Prompt Learning
An empirical study showing that graph prompt learning exposes node attributes and links to inference attacks, with prompt tuning adding little extra risk over frozen GNN baselines.