Privacy Amplification by Sampling under User-level Differential Privacy

Summary: Explores privacy amplification by sampling under user-level DP for data management. Analyzes two strategies—simple sampling and sample-and-explore—providing amplification bounds and practical noise reductions with empirical viability on large private datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6905
Venue: SIGMOD
Year: 2024
Pagerank: 5.6124452e-05
Overall Rank: 7,456 | 48.85%
DOI: 10.1145/3639289

Incoming Non-self Citations Over Time

Authors

1. Juanru Fang (Hong Kong University of Science and Technology)
2. Ke Yi (Hong Kong University of Science and Technology)

BibTeX Citation

@inproceedings{fang_sigmod24,
        title = {{Privacy Amplification by Sampling under User-level Differential Privacy}},
        author = {Fang, Juanru and Yi, Ke},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639289},
        url = {https://dl.acm.org/doi/10.1145/3639289},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,249	Femur: A Flexible Framework for Fast and Secure Querying from Public Key-Value Store	2025	SIGMOD	5.4574671e-05
10,224	DP-S4S: Accurate and Scalable Select-Join-Aggregate Query Processing with User-Level Differential Privacy	2026	SIGMOD	5.093636e-05
10,914	Calibrating Noise for Group Privacy in Subsampled Mechanisms	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
131	Ripple Joins for Online Aggregation	1999	SIGMOD	0.00030424509
593	Wander Join: Online Aggregation via Random Walks	2016	SIGMOD	0.00016027871
596	Private Analysis of Graph Structure	2011	VLDB	0.00015926024
737	Join Size Estimation Subject to Filter Conditions	2015	VLDB	0.00014490983
836	Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins	2013	SIGMOD	0.00013715654
1,144	PrivateSQL: A Differentially Private SQL Query Engine	2019	VLDB	0.00011999046
1,790	Publishing Graph Degree Distribution with Node Differential Privacy	2016	SIGMOD	9.7502278e-05
1,960	Private Release of Graph Statistics using Ladder Functions	2015	SIGMOD	9.4058693e-05
2,436	Computing Local Sensitivities of Counting Queries with Joins	2020	SIGMOD	8.5806427e-05
4,394	R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys	2022	SIGMOD	6.7274063e-05
7,292	A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries	2022	PODS	5.653597e-05

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#	Overall Rank	Paper	Year	Venue
1	11,280	Confidence Intervals for Private Query Processing	2024	VLDB
2	836	Recursive Mechanism: Towards Node Differential Privacy and Unrestricted Joins	2013	SIGMOD
3	5,439	Improving Utility and Security of the Shuffler-based Differential Privacy	2020	VLDB
4	6,441	Differential Privacy in Data Publication and Analysis	2012	SIGMOD
5	218	Limiting Privacy Breaches in Privacy Preserving Data Mining	2003	PODS
6	5,595	Privacy Amplification via Shuffling: Unified, Simplified, and Tightened	2024	VLDB
7	1,504	A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy	2014	VLDB
8	11,203	Personalized Truncation for Personalized Privacy	2024	SIGMOD
9	10,335	A General Framework for Per-record Differential Privacy	2026	SIGMOD
10	10,224	DP-S4S: Accurate and Scalable Select-Join-Aggregate Query Processing with User-Level Differential Privacy	2026	SIGMOD