Arpana Hosabettu
Engineer on Private Ads Measurement at Google
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On the Differential Privacy and Interactivity of Privacy Sandbox Reports
Charlie Harrison
Pritish Kamath
Alexander Knop
Ethan Leeman
Vikas Sahu
Phillipp Schoppmann
PETS (2025)
Preview abstract
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.
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