On the Differential Privacy and Interactivity of Privacy Sandbox Reports
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910900077723648 |
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| author | Ghazi, Badih Harrison, Charlie Hosabettu, Arpana Kamath, Pritish Knop, Alexander Kumar, Ravi Leeman, Ethan Manurangsi, Pasin Raykova, Mariana Sahu, Vikas Schoppmann, Phillipp |
| author_facet | Ghazi, Badih Harrison, Charlie Hosabettu, Arpana Kamath, Pritish Knop, Alexander Kumar, Ravi Leeman, Ethan Manurangsi, Pasin Raykova, Mariana Sahu, Vikas Schoppmann, Phillipp |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_16916 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | On the Differential Privacy and Interactivity of Privacy Sandbox Reports Ghazi, Badih Harrison, Charlie Hosabettu, Arpana Kamath, Pritish Knop, Alexander Kumar, Ravi Leeman, Ethan Manurangsi, Pasin Raykova, Mariana Sahu, Vikas Schoppmann, Phillipp Cryptography and Security 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. |
| title | On the Differential Privacy and Interactivity of Privacy Sandbox Reports |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2412.16916 |