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cs.CR2026
Bayesian Membership Privacy for Graph Neural Networks
Sinan Yıldırım, Megha Khosla
Existing privacy analyses for Graph Neural Networks (GNNs) largely inherit assumptions from non-graph settings, overlooking structural correlations and stochastic training-graph sa…
cs.LG2026
Impact of Graph Structure on Membership-Inference Risk for Graph Neural Networks
Megha Khosla
Graph neural networks (GNNs) are widely used for tasks such as node classification and link prediction, but their use in sensitive settings raises concerns about training-data leak…