On the Differential Privacy and Interactivity of Privacy Sandbox Reports
The Privacy Sandbox initiative from Google includes APIs for enabling privacy-preserving advertising functionalities as part of the effort to limit third-party cookies. In particular, the Private Aggregation API (PAA) and the Attribution Reporting API (ARA) can be used for ad measurement while providing different guardrails for safeguarding user privacy, including a framework for satisfying differential privacy (DP). In this work, we provide an abstract model for analyzing the privacy of these APIs and show that they satisfy a formal DP guarantee under certain assumptions. Our analysis handles the case where both the queries and database can change interactively based on previous responses from the API.
Authors
- Pasin Manurangsi (ORCID: https://orcid.org/0000-0002-1052-2801)
- Badih Ghazi (ORCID: https://orcid.org/0000-0001-8254-3268)
- Alexander Knop (ORCID: https://orcid.org/0000-0003-4311-9071)
- Phillipp Schoppmann (ORCID: https://orcid.org/0000-0001-7951-3930)
- Ethan Leeman
- Vikas Kumar Sahu (ORCID: https://orcid.org/0000-0002-1644-5704)
- Charlie Harrison
- Mariana Raykova (ORCID: https://orcid.org/0000-0002-1744-4025)
- Ravi Kumar (ORCID: https://orcid.org/0000-0002-2203-2586)
- Pritish Kamath
- Arpana Hosabettu (ORCID: https://orcid.org/0009-0005-8140-211X)
Institutions
- Google (United States) (US)
Publication Details
- Journal
- Proceedings on Privacy Enhancing Technologies
- Published
- 2025-05-19
- DOI
- https://doi.org/10.56553/popets-2025-0104
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.00