GUPT: Privacy Preserving Data Analysis Made Easy
Summary: GUPT enables privacy-preserving data analysis by external agents without reengineering programs or trusting the analysis code. It provides differential privacy for arbitrary code, resists side-channel leaks, and uses a time-decay data-sensitivity model to allocate privacy levels and boost utility. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Prashanth Mohan
- 2. Abhradeep Thakurta
- 3. Elaine Shi
- 4. Dawn Song
- 5. David E. Culler
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 77 | An Amateur's Introduction to Recursive Query Processing Strategies | 1986 | SIGMOD | 0.00057043861 |
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |
| 178 | Boosting the Accuracy of Differentially Private Histograms Through Consistency | 2010 | VLDB | 0.00037697111 |
| 642 | Private Analysis of Graph Structure | 2011 | VLDB | 0.00018755196 |
| 715 | Differentially Private Aggregation of Distributed Time-Series with Transformation and Encryption | 2010 | SIGMOD | 0.00017725693 |
| 742 | Optimizing Linear Counting Queries Under Differential Privacy | 2010 | PODS | 0.00017360873 |
| 2,406 | Attacks on Privacy and deFinetti's Theorem | 2009 | SIGMOD | 8.8811954e-05 |
| 2,776 | iReduct: Differential Privacy with Reduced Relative Errors | 2011 | SIGMOD | 8.1326122e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 453 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.00022741848 |
| 7,417 | DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance | 2023 | SIGMOD | 4.7355114e-05 |
| 2,806 | CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers | 2020 | SIGMOD | 8.0911177e-05 |
| 955 | Privacy Preserving OLAP | 2005 | SIGMOD | 0.00015075131 |
| 1,738 | PrivateSQL: A Differentially Private SQL Query Engine | 2019 | VLDB | 0.00010720057 |
| 11,112 | DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System | 2024 | VLDB | 4.1945683e-05 |
| 6,486 | Differential Privacy in Data Publication and Analysis | 2012 | SIGMOD | 5.0445043e-05 |
| 6,970 | Architecting a Differentially Private SQL Engine | 2019 | CIDR | 4.8796169e-05 |
| 10,041 | A General Framework for Per-record Differential Privacy | 2026 | SIGMOD | 4.1945683e-05 |
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |