{
  "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.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.25155",
  "author_total": 7,
  "authors": [
    {
      "name": "Anum Fatima"
    },
    {
      "name": "Stratis Limnios"
    },
    {
      "name": "James Adams"
    },
    {
      "name": "Lukasz Szpruch"
    },
    {
      "name": "Carsten Maple"
    },
    {
      "name": "Gesine Reinert"
    },
    {
      "name": "Andrew Elliott"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7jpbnt7pamaxm.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.25155",
  "fulltext_url": null,
  "id": "7jpbnt7pamaxm",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.25155",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "stat.ML"
    ],
    [
      "openalex",
      "1702|Privacy-Preserving Technologies in Data"
    ]
  ],
  "openalex": "W7214092193",
  "pdf_url": "https://arxiv.org/pdf/2609.25155",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7jpbnt7pamaxm.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:49Z",
      "native_id": "2609.25155",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.25155"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ML",
      "subfield": "statistics"
    }
  ],
  "title": "Empirical Auditing of Edge-Private Graph Generators",
  "title_text": "Empirical Auditing of Edge-Private Graph Generators",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:49Z",
  "url": "https://research.draconitic.com/paper/7jpbnt7pamaxm",
  "venue": "arXiv",
  "versions": []
}