# On the Differential Privacy and Interactivity of Privacy Sandbox Reports

arXiv: https://arxiv.org/abs/2412.16916 · HTML: https://mlsanity.com/paper/2412.16916/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2024.

## Built on by (most cited first, 2 of 2)

- [Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss](https://mlsanity.com/paper/2606.03878/) (2026)
- [Differentially Private Synthetic Data Release for Topics API Outputs](https://mlsanity.com/paper/2506.23855/) (2025)

## Abstract (arXiv)

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.