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arxiv: 2412.16916 · v3 · pith:WEGOMOEOnew · submitted 2024-12-22 · 💻 cs.CR

On the Differential Privacy and Interactivity of Privacy Sandbox Reports

classification 💻 cs.CR
keywords privacyapisdifferentialsandboxabstractadvertisingaggregationanalysis
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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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Cited by 1 Pith paper

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  1. Big Bird: Resilient Privacy Budgeting Across Untrusted Web Domains

    cs.CR 2025-06 unverdicted novelty 6.0

    Big Bird enforces global device-epoch individual differential privacy for multi-querier Attribution by tying privacy-loss quotas to a stock-and-flow model of impressions and conversions with per-user-action caps.