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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
6358
Venue
SIGMOD
Year
2022
Pagerank
6.7274063e-05
Overall Rank
4,394 | 69.86%
DOI
10.1145/3514221.3517844

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{dong_sigmod22,
        title = {{R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys}},
        author = {Dong, Wei and Fang, Juanru and Yi, Ke and Tao, Yuchao and Machanavajjhala, Ashwin},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3517844},
        url = {https://dl.acm.org/doi/10.1145/3514221.3517844},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 27 of 27 citing papers.

Rank Citing Paper Year Venue Pagerank
4,827 PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy 2023 SIGMOD 6.4895329e-05
6,376 DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance 2023 SIGMOD 5.893174e-05
6,534 Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy 2023 SIGMOD 5.8486828e-05
7,292 A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries 2022 PODS 5.653597e-05
7,456 Privacy Amplification by Sampling under User-level Differential Privacy 2024 SIGMOD 5.6124452e-05
7,850 Differentially Private Data Release over Multiple Tables 2023 PODS 5.5316993e-05
8,158 Continual Observation of Joins under Differential Privacy 2024 SIGMOD 5.4756587e-05
8,503 Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense 2024 VLDB 5.4132367e-05
8,719 DPXPlain: Privately Explaining Aggregate Query Answers 2023 VLDB 5.3774243e-05
9,171 DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries 2023 SIGMOD 5.3093185e-05
9,785 Secure Sampling for Approximate Multi-party Query Processing 2023 SIGMOD 5.2209769e-05
10,188 Acyclic Graph Pattern Counting under Local Differential Privacy 2026 SIGMOD 5.093636e-05
10,221 Differentially Oblivious Multi-way Join 2026 SIGMOD 5.093636e-05
10,224 DP-S4S: Accurate and Scalable Select-Join-Aggregate Query Processing with User-Level Differential Privacy 2026 SIGMOD 5.093636e-05
10,335 A General Framework for Per-record Differential Privacy 2026 SIGMOD 5.093636e-05
10,385 N2E: A General Framework to Reduce Node-Differential Privacy to Edge-Differential Privacy for Graph Analytics 2026 SIGMOD 5.093636e-05
10,442 Defense against Poisoning Attacks under Shuffle-DP 2026 SIGMOD 5.093636e-05
10,786 Computing Inconsistency Measures Under Differential Privacy 2025 SIGMOD 5.093636e-05
10,803 SPECIAL: SynoPsis AssistEd Secure CollaboratIve AnaLytics 2025 VLDB 5.093636e-05
10,914 Calibrating Noise for Group Privacy in Subsampled Mechanisms 2025 VLDB 5.093636e-05
10,967 Privacy-Enhanced Database Synthesis for Benchmark Publishing 2025 VLDB 5.093636e-05
11,203 Personalized Truncation for Personalized Privacy 2024 SIGMOD 5.093636e-05
11,280 Confidence Intervals for Private Query Processing 2024 VLDB 5.093636e-05
11,318 DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System 2024 VLDB 5.093636e-05
11,349 DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms 2024 VLDB 5.093636e-05
11,369 Universal Private Estimators 2023 PODS 5.093636e-05
11,480 Explaining Differentially Private Query Results With DPXPlain 2023 VLDB 5.093636e-05
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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.

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