Back to papers
R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys
Summary: Presents R2T, the first DP mechanism for SPJA queries with foreign-key constraints (node-DP graph-pattern counting). Offers an instance-optimal truncation framework, deployable on any RDBMS, delivering strong utility gains over prior DP methods.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6296
- Venue
- SIGMOD
- Year
- 2022
- Pagerank
- 5.4776364e-05
- Overall Rank
- 5,491 | 61.81%
- DOI
-
10.1145/3514221.3517844
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 24 of 24 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 5,349 |
PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy |
2023 |
SIGMOD |
5.553869e-05 |
| 5,885 |
Continual Observation of Joins under Differential Privacy |
2024 |
SIGMOD |
5.2880878e-05 |
| 7,417 |
DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance |
2023 |
SIGMOD |
4.7355114e-05 |
| 7,439 |
Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy |
2023 |
SIGMOD |
4.7304034e-05 |
| 7,579 |
A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries |
2022 |
PODS |
4.706055e-05 |
| 7,864 |
Differentially Private Data Release over Multiple Tables |
2023 |
PODS |
4.6327272e-05 |
| 8,510 |
Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense |
2024 |
VLDB |
4.4952414e-05 |
| 8,873 |
Privacy Amplification by Sampling under User-level Differential Privacy |
2024 |
SIGMOD |
4.4313867e-05 |
| 9,652 |
Secure Sampling for Approximate Multi-party Query Processing |
2023 |
SIGMOD |
4.3109001e-05 |
| 9,766 |
DPXPlain: Privately Explaining Aggregate Query Answers |
2023 |
VLDB |
4.2856106e-05 |
| 9,796 |
DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries |
2023 |
SIGMOD |
4.2818172e-05 |
| 10,041 |
A General Framework for Per-record Differential Privacy |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,094 |
N2E: A General Framework to Reduce Node-Differential Privacy to Edge-Differential Privacy for Graph Analytics |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,153 |
Defense against Poisoning Attacks under Shuffle-DP |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,513 |
Computing Inconsistency Measures Under Differential Privacy |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,531 |
SPECIAL: Synopsis Assisted Secure Collaborative Analytics |
2025 |
VLDB |
4.1945683e-05 |
| 10,664 |
Calibrating Noise for Group Privacy in Subsampled Mechanisms |
2025 |
VLDB |
4.1945683e-05 |
| 10,724 |
Privacy-Enhanced Database Synthesis for Benchmark Publishing |
2025 |
VLDB |
4.1945683e-05 |
| 10,992 |
Personalized Truncation for Personalized Privacy |
2024 |
SIGMOD |
4.1945683e-05 |
| 11,074 |
Confidence Intervals for Private Query Processing |
2024 |
VLDB |
4.1945683e-05 |
| 11,112 |
DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System |
2024 |
VLDB |
4.1945683e-05 |
| 11,143 |
DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms |
2024 |
VLDB |
4.1945683e-05 |
| 11,163 |
Universal Private Estimators |
2023 |
PODS |
4.1945683e-05 |
| 11,281 |
Explaining Differentially Private Query Results With DPXPlain |
2023 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 83 |
Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis |
2009 |
SIGMOD |
0.00053933811 |
| 111 |
Privacy, Accuracy, and Consistency Too: A Holistic Solution to Contingency Table Release |
2007 |
PODS |
0.00047073785 |
| 453 |
Towards Practical Differential Privacy for SQL Queries |
2018 |
VLDB |
0.00022741848 |
| 642 |
Private Analysis of Graph Structure |
2011 |
VLDB |
0.00018755196 |
| 719 |
Understanding Hierarchical Methods for Differentially Private Histograms |
2013 |
VLDB |
0.00017626484 |
| 1,177 |
Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins |
2013 |
SIGMOD |
0.00013470212 |
| 1,602 |
Calibrating Data to Sensitivity in Private Data Analysis: A Platform for Differentially-Private Analysis of Weighted Datasets |
2014 |
VLDB |
0.00011199166 |
| 1,738 |
PrivateSQL: A Differentially Private SQL Query Engine |
2019 |
VLDB |
0.00010720057 |
| 1,764 |
PriView: Practical Differentially Private Release of Marginal Contingency Tables |
2014 |
SIGMOD |
0.00010636626 |
| 2,226 |
Publishing Graph Degree Distribution with Node Differential Privacy |
2016 |
SIGMOD |
9.2421776e-05 |
| 2,683 |
Private Release of Graph Statistics using Ladder Functions |
2015 |
SIGMOD |
8.315553e-05 |
| 3,104 |
Computing Local Sensitivities of Counting Queries with Joins |
2020 |
SIGMOD |
7.5578613e-05 |
| 7,064 |
Residual Sensitivity for Differentially Private Multi-Way Joins |
2021 |
SIGMOD |
4.8450749e-05 |
| 7,579 |
A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries |
2022 |
PODS |
4.706055e-05 |
Semantically Similar Papers