On the Differential Privacy and Interactivity of Privacy Sandbox Reports

Badih Ghazi; Charlie Harrison; Arpana Hosabettu; Pritish Kamath; Alexander Knop; Ravi Kumar; Ethan Leeman; Pasin Manurangsi; Mariana Raykova; Vikas Sahu; Phillipp Schoppmann

arXiv · 2412.16916

On the Differential Privacy and Interactivity of Privacy Sandbox Reports

Badih Ghazi·Charlie Harrison·Arpana Hosabettu·Pritish Kamath·Alexander Knop·Ravi Kumar·Ethan Leeman·Pasin Manurangsi·Mariana Raykova·Vikas Sahu·Phillipp Schoppmann

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Abstract

The Privacy Sandbox initiative from Google includes APIs for enabling privacy-preserving advertising functionalities as part of the effort around limiting 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.

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BibTeX RIS

Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Mariana Raykova, Vikas Sahu, Phillipp Schoppmann. 2024-12-22. On the Differential Privacy and Interactivity of Privacy Sandbox Reports. https://arxiv.org/abs/2412.16916

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