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Continual Observation of Joins under Differential Privacy

Summary: Differentially private continual-observation mechanism for arbitrary join queries/predicates, extending beyond prior graph-pattern-only work. Key novelty: no predeclared degree/frequency bounds; error adapts to the current instance’s max degree/frequency, yielding instance-specific utility over infinite streams. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID
h53a65c33ea2f3fc4
Venue
SIGMOD
Year
2024
Pagerank
5.3502656e-05
Overall Rank
8,338 | 43.96%
DOI
10.1145/3654931
PDF
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Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{dong_sigmod24,
        title = {{Continual Observation of Joins under Differential Privacy}},
        author = {Dong, Wei and Chen, Zijun and Luo, Qiyao and Shi, Elaine and Yi, Ke},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654931},
        url = {https://dl.acm.org/doi/10.1145/3654931},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 19 of 19 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
609 Private Analysis of Graph Structure 2011 VLDB 0.0001558459
685 Trill: A High-Performance Incremental Query Processor for Diverse Analytics 2015 VLDB 0.00014778299
854 Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins 2013 SIGMOD 0.00013435506
1,091 What do Shannon-type Inequalities, Submodular Width, and Disjunctive Datalog have to do with one another? 2017 PODS 0.00012068611
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
2,012 Private Release of Graph Statistics using Ladder Functions 2015 SIGMOD 9.190805e-05
2,488 Computing Local Sensitivities of Counting Queries with Joins 2020 SIGMOD 8.3933335e-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
5,061 Change Propagation Without Joins 2023 VLDB 6.2897936e-05
6,665 Better than Composition: How to Answer Multiple Relational Queries under Differential Privacy 2023 SIGMOD 5.7147475e-05
6,808 Residual Sensitivity for Differentially Private Multi-Way Joins 2021 SIGMOD 5.6756613e-05
7,442 A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries 2022 PODS 5.5241292e-05
8,954 Differentially Private Stream Processing at Scale 2024 VLDB 5.2510221e-05
11,611 Confidence Intervals for Private Query Processing 2024 VLDB 4.9769913e-05
11,691 Universal Private Estimators 2023 PODS 4.9769913e-05
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