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arXiv · 2609.25155

Empirical Auditing of Edge-Private Graph Generators

Anum Fatima·Stratis Limnios·James Adams·Lukasz Szpruch·Carsten Maple·Gesine Reinert·Andrew Elliott
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Abstract

We empirically audit privacy leakage by testing whether outputs from edge-neighbouring inputs remain distinguishable, using statistically valid lower bounds on the privacy loss witnessed by our attacks. Our framework compares direct-edge, local-structural, and GNN-based attacks through the geometry surrounding a target edge. Experiments across two generators and two networks show that privacy leakage is both mechanism- and network-dependent, with learned representations revealing information not captured by conventional local statistics.

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Anum Fatima, Stratis Limnios, James Adams, Lukasz Szpruch, Carsten Maple, Gesine Reinert, Andrew Elliott. 2026-09-21. Empirical Auditing of Edge-Private Graph Generators. https://arxiv.org/abs/2609.25155

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