{
  "id": 7852,
  "url": "https://doi.org/10.1371/journal.pone.0120592",
  "title": "A Game Theoretic Framework for Analyzing Re-Identification Risk",
  "summary": "Given the potential wealth of insights in personal data the big databases can provide, many organizations aim to share data while protecting privacy by sharing de-identified data, but are concerned because various demonstrations show such data can be re-identified. Yet these investigations focus on how attacks can be perpetrated, not the likelihood they will be realized. This paper introduces a game theoretic framework that enables a publisher to balance re-identification risk with the value of ",
  "authors": "Zhiyu Wan, Yevgeniy Vorobeychik, Weiyi Xia, Ellen Wright Clayton, Murat Kantarcıoğlu, Ranjit Ganta",
  "category": "research",
  "topics": "privacy-surveillance,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2015-03-25T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:27.494Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7852",
  "original_url": "https://doi.org/10.1371/journal.pone.0120592",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}