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Persuasive Privacy

Author

Listed:
  • Joshua J Bon
  • James Bailie
  • Judith Rousseau
  • Christian P Robert

Abstract

We propose a novel framework for measuring privacy from a Bayesian game-theoretic perspective. This framework enables the creation of new, purpose-driven privacy definitions that are rigorously justified, while also allowing for the assessment of existing privacy guarantees through game theory. We show that pure and probabilistic differential privacy are special cases of our framework, and provide new interpretations of the post-processing inequality in this setting. Further, we demonstrate that privacy guarantees can be established for deterministic algorithms, which are overlooked by current privacy standards.

Suggested Citation

  • Joshua J Bon & James Bailie & Judith Rousseau & Christian P Robert, 2026. "Persuasive Privacy," Papers 2601.22945, arXiv.org.
    • Handle: RePEc:arx:papers:2601.22945
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    References listed on IDEAS

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    1. Robert J. Aumann, 2025. "Correlated Equilibrium as an Expression of Bayesian Rationality," World Scientific Book Chapters, in: SELECTED CONTRIBUTIONS TO GAME THEORY, chapter 7, pages 175-200, World Scientific Publishing Co. Pte. Ltd..
    2. Matthew J. Schneider & James Bailie & Dawn Iacobucci, 2025. "Why Data Anonymization Has Not Taken Off," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 12(1), pages 1-8, December.
    3. Jonas R. Brehmer & Tilmann Gneiting, 2020. "Properization: constructing proper scoring rules via Bayes acts," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 659-673, June.
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