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DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance

Summary: DProvDB introduces fine-grained privacy provenance for multi-analyst differential privacy. It tracks per-analyst privacy loss and allocates the budget by privilege level, maximizing the number of accurately answered queries under a fixed budget (non-colluding). (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h19f2525c2fcc9789
Venue
SIGMOD
Year
2023
Pagerank
5.7582198e-05
Overall Rank
6,507 | 56.27%
DOI
10.1145/3626761

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhang_sigmod23,
        title = {{DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance}},
        author = {Zhang, Shufan and He, Xi},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3626761},
        url = {https://dl.acm.org/doi/10.1145/3626761},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
8,427 Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value Store 2025 SIGMOD 5.3324907e-05
9,080 Privacy and Accuracy-Aware AI/ML Model Deduplication 2025 SIGMOD 5.2258409e-05
10,452 DP-S4S: Accurate and Scalable Select-Join-Aggregate Query Processing with User-Level Differential Privacy 2026 SIGMOD 4.9769913e-05
11,550 Personalized Truncation for Personalized Privacy 2024 SIGMOD 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 22 of 22 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
64 Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis 2009 SIGMOD 0.00038504258
276 Towards Practical Differential Privacy for SQL Queries 2018 VLDB 0.00022332903
1,168 PrivateSQL: A Differentially Private SQL Query Engine 2019 VLDB 0.00011725733
1,243 Calibrating Data to Sensitivity in Private Data Analysis: A Platform for Differentially-Private Analysis of Weighted Datasets 2014 VLDB 0.00011372988
2,371 Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies 2014 SIGMOD 8.5575829e-05
2,855 iReduct: Differential Privacy with Reduced Relative Errors 2011 SIGMOD 7.93537e-05
3,176 CGM: An Enhanced Mechanism for Streaming Data Collection with Local Differential Privacy 2021 VLDB 7.5642412e-05
4,414 ϵktelo: A Framework for Defining Differentially-Private Computations 2018 SIGMOD 6.6080858e-05
4,498 R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys 2022 SIGMOD 6.5733482e-05
4,947 PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy 2023 SIGMOD 6.3409221e-05
5,185 APEx: Accuracy-Aware Differentially Private Data Exploration 2019 SIGMOD 6.2362923e-05
6,541 Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy 2022 VLDB 5.7506473e-05
6,808 Residual Sensitivity for Differentially Private Multi-Way Joins 2021 SIGMOD 5.6756613e-05
7,299 Architecting a Differentially Private SQL Engine 2019 CIDR 5.5599778e-05
7,800 Budget Sharing for Multi-Analyst Differential Privacy 2021 VLDB 5.4490561e-05
8,013 Differentially Private Data Release over Multiple Tables 2023 PODS 5.4050229e-05
8,139 Optimizing Fitness-For-Use of Differentially Private Linear Queries 2021 VLDB 5.3905499e-05
8,995 Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration 2023 VLDB 5.2405299e-05
9,783 Answering Private Linear Queries Adaptively using the Common Mechanism 2023 VLDB 5.1285234e-05
9,784 Multi-Analyst Differential Privacy for Online Query Answering 2023 VLDB 5.1285234e-05
9,785 Framework for Differentially Private Data Analysis with Multiple Accuracy Requirements 2021 SIGMOD 5.1285234e-05
10,030 Don’t Be a Tattle-Tale: Preventing Leakages through Data Dependencies on Access Control Protected Data 2022 VLDB 5.0910473e-05
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# Overall Rank Paper Year Venue
1 9,785 Framework for Differentially Private Data Analysis with Multiple Accuracy Requirements 2021 SIGMOD
2 6,808 Residual Sensitivity for Differentially Private Multi-Way Joins 2021 SIGMOD
3 9,784 Multi-Analyst Differential Privacy for Online Query Answering 2023 VLDB
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5 10,550 A General Framework for Per-record Differential Privacy 2026 SIGMOD
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7 11,642 DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System 2024 VLDB
8 276 Towards Practical Differential Privacy for SQL Queries 2018 VLDB
9 1,168 PrivateSQL: A Differentially Private SQL Query Engine 2019 VLDB
10 7,299 Architecting a Differentially Private SQL Engine 2019 CIDR