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)
Incoming Non-self Citations Over Time
Authors
- 1. Wei Dong (Carnegie Mellon University)
- 2. Zijun Chen (Hong Kong University of Science and Technology)
- 3. Qiyao Luo (Hong Kong University of Science and Technology)
- 4. Elaine Shi (Carnegie Mellon University)
- 5. Ke Yi (Hong Kong University of Science and Technology)
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.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,188 | Acyclic Graph Pattern Counting under Local Differential Privacy | 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 |
| 10,391 | Privacy-preserving and Verifiable Causal Prescriptive Analytics | 2026 | SIGMOD | 5.093636e-05 |
| 10,759 | Efficient and Accurate Differentially Private Cardinality Continual Releases | 2025 | SIGMOD | 5.093636e-05 |
| 11,318 | DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System | 2024 | VLDB | 5.093636e-05 |
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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.
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