On the Differential Privacy and Interactivity of Privacy Sandbox Reports

TL;DR

This paper analyzes the Privacy Sandbox APIs, specifically PAA and ARA, demonstrating they satisfy differential privacy guarantees even under interactive query and database updates.

Contribution

It provides an abstract model for analyzing privacy guarantees of these APIs and proves their differential privacy compliance under interactive conditions.

Findings

APIs satisfy formal differential privacy guarantees

Analysis handles interactive query and database updates

Framework for privacy analysis of sandbox APIs

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.