Proving Differential Privacy via Probabilistic Couplings

Author:

Barthe Gilles1,Gaboardi Marco2,Grégoire Benjamin3,Hsu Justin4,Strub Pierre-Yves1

Affiliation:

1. IMDEA Software

2. University at Buffalo, SUNY

3. Inria

4. University of Pennsylvania

Funder

National Science Foundation

Simons Foundation

Engineering and Physical Sciences Research Council

Publisher

ACM

Cited by 50 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Asynchronous Probabilistic Couplings in Higher-Order Separation Logic;Proceedings of the ACM on Programming Languages;2024-01-05

2. Deciding Differential Privacy of Online Algorithms with Multiple Variables;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

3. Assume but Verify: Deductive Verification of Leaked Information in Concurrent Applications;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

4. Detecting Violations of Differential Privacy for Quantum Algorithms;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

5. A Novel Analysis of Utility in Privacy Pipelines, Using Kronecker Products and Quantitative Information Flow;Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security;2023-11-15

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