On the Differential Privacy and Interactivity of Privacy Sandbox Reports

• URL: http://arxiv.org/abs/2412.16916v1
• Date: Sun, 22 Dec 2024 08:22:57 GMT
• Title: On the Differential Privacy and Interactivity of Privacy Sandbox Reports
• Authors: Badih Ghazi, Charlie Harrison, Arpana Hosabettu, Pritish Kamath, Alexander Knop, Ravi Kumar, Ethan Leeman, Pasin Manurangsi, Vikas Sahu,
• Abstract summary: The Privacy Sandbox initiative from Google includes APIs for enabling privacy-preserving advertising functionalities. We provide a formal model for analyzing the privacy of these APIs and show that they satisfy a formal DP guarantee.
• Score: 78.21466601986265
• License:
• 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 a formal 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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