DP4SQL: Differentially Private SQL with Flexible Privacy Policies

Computer Science > Cryptography and Security [Submitted on 5 Jun 2026] DP4SQL: Differentially Private SQL with Flexible Privacy Policies Andrew Cascio, KinChin Tong, Daniel Kifer, Zeyu Ding, Danfeng Zhang The plausible deniability model of differential privacy for single-table datasets is well-understood. However, applying differential privacy to relational databases is much trickier: each application needs flexibility in specifying the pieces of information about an entity, spread across multiple relations, that require plausible deniability guarantees. Existing differentially private SQL systems only support rigid privacy policies. Even seemingly small changes, such as specifying that some tables need to protect the existence of records while others only need to protect the record contents, require significant manual effort in updating their privacy accountants and proving their correctness. One example of a challenge is the presence of partially public data. Public columns in a table (e.g., faculty names in a university dataset and partial course enrollment information) can cause some queries to require more noise (compared to fully private data), while others require less noise. This kind of reasoning is not supported in existing systems. Another example is when different parts of records (e.g., demographics, financial data) require different levels of privacy protection. Again, existing differentially private SQL systems need to rewrite their rules for calculating query stability in order to support such a feature. This paper presents DP4SQL, a differentially private SQL system that allows data curators to better customize the plausible deniability requirements for their relational databases. This avoids the drawbacks of the "one-size-fits-all" systems that would either underprotect the data or inject too much noise into query answers. Comments: 17 pages Subjects: Cryptography and Security (cs.CR); Databases (cs.DB) Cite as: arXiv:2606.07883 [cs.CR]   (or arXiv:2606.07883v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2606.07883 Focus to learn more Submission history From: Andrew Cascio [view email] [v1] Fri, 5 Jun 2026 22:35:35 UTC (250 KB) Access Paper: view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-06 Change to browse by: cs cs.DB References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)