Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis
Summary: PINQ is an extensible platform for privacy-preserving data analysis that enforces end-to-end differential privacy via a declarative SQL-like language. The platform provides unconditional DP guarantees, letting analysts work on raw data with only aggregated outputs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 27 of 77 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 40 | Privacy-Preserving Data Mining | 2000 | SIGMOD | 0.00074232718 |
| 111 | Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release | 2007 | PODS | 0.00047073785 |
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.00032707646 |
| 568 | Practical Privacy: The SuLQ Framework | 2005 | PODS | 0.00019949368 |
| 634 | m-Invariance: Towards Privacy Preserving Re-publication of Dynamic Datasets | 2007 | SIGMOD | 0.00018895628 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,668 | PrivateClean: Data Cleaning and Differential Privacy | 2016 | SIGMOD | 6.0115918e-05 |
| 7,064 | Residual Sensitivity for Differentially Private Multi-Way Joins | 2021 | SIGMOD | 4.8450749e-05 |
| 10,041 | A General Framework for Per-record Differential Privacy | 2026 | SIGMOD | 4.1945683e-05 |
| 1,681 | GUPT: Privacy Preserving Data Analysis Made Easy | 2012 | SIGMOD | 0.00010929746 |
| 6,486 | Differential Privacy in Data Publication and Analysis | 2012 | SIGMOD | 5.0445043e-05 |
| 7,417 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 4.7355114e-05 |
| 453 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.00022741848 |
| 1,602 | Calibrating Data to Sensitivity in Private Data Analysis: A Platform for Differentially-Private Analysis of Weighted Datasets | 2014 | VLDB | 0.00011199166 |
| 6,970 | Architecting a Differentially Private SQL Engine | 2019 | CIDR | 4.8796169e-05 |
| 1,738 | PrivateSQL: A Differentially Private SQL Query Engine | 2019 | VLDB | 0.00010720057 |