DP-PQD: Privately Detecting Per-Query Gaps In Synthetic Data Generated By Black-Box Mechanisms

Summary: DP-PQD: a differentially-private framework to detect per-query gaps between private and black-box synthetic datasets, deciding if a count/sum/median is within a user-specified threshold. Provides private algorithms, theoretical guarantees, and empirical validation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13743
Venue: VLDB
Year: 2024
Pagerank: 4.1945683e-05
Overall Rank: 11,143 | 22.49%
DOI: 10.14778/3617838.3617844

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,513	Computing Inconsistency Measures Under Differential Privacy	2025	SIGMOD	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
742	Optimizing Linear Counting Queries Under Differential Privacy	2010	PODS	0.00017360873
2,421	Data Synthesis based on Generative Adversarial Networks	2018	VLDB	8.8514021e-05
2,434	Optimizing error of high-dimensional statistical queries under differential privacy	2018	VLDB	8.8278955e-05
2,758	Understanding the Sparse Vector Technique for Differential Privacy	2017	VLDB	8.1653216e-05
2,881	Data Synthesis via Differentially Private Markov Random Fields	2021	VLDB	7.9665978e-05
3,329	AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data	2022	VLDB	7.2156424e-05
3,831	Kamino: Constraint-Aware Differentially Private Data Synthesis	2021	VLDB	6.7181688e-05
5,491	R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys	2022	SIGMOD	5.4776364e-05
5,872	Differential Privacy and the US Census	2019	PODS	5.2937278e-05
7,502	PSynDB: Accurate and Accessible Private Data Generation	2019	VLDB	4.7180617e-05

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