Persuasive Privacy
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866913177341526016 |
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| author | Bon, Joshua J Bailie, James Rousseau, Judith Robert, Christian P |
| author_facet | Bon, Joshua J Bailie, James Rousseau, Judith Robert, Christian P |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_22945 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Persuasive Privacy Bon, Joshua J Bailie, James Rousseau, Judith Robert, Christian P Statistics Theory Cryptography and Security Theoretical Economics 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. |
| title | Persuasive Privacy |
| topic | Statistics Theory Cryptography and Security Theoretical Economics |
| url | https://arxiv.org/abs/2601.22945 |