Synthetic Tabular Data: Methods, Attacks and Defenses

Summary: Tutorial survey of tabular synthetic-data generation, spanning probabilistic graphical models and deep learning. Examines privacy limitations through attacks recovering information from training data, and discusses defenses, extensions, and open problems. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 14367
Venue: VLDB
Year: 2025
Pagerank: 5.4119882e-05
Overall Rank: 8,514 | 41.59%
DOI: 10.14778/3750601.3750692

Incoming Non-self Citations Over Time

Authors

1. Graham Cormode (Meta; University of Warwick)
2. Shripad Gade (Meta)
3. Samuel Maddock (Meta; University of Warwick)
4. Enayat Ullah (Meta)

BibTeX Citation

@article{cormode_vldb25,
        title = {{Synthetic Tabular Data: Methods, Attacks and Defenses}},
        author = {Cormode, Graham and Gade, Shripad and Maddock, Samuel and Ullah, Enayat},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {12},
        pages = {5448--5450},
        doi = {10.14778/3750601.3750692},
        url = {https://doi.org/10.14778/3750601.3750692},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,550	Understanding Disclosure Risk in Differential Privacy with Applications to Noise Calibration and Auditing	2026	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
2,476	Data Synthesis via Differentially Private Markov Random Fields	2021	VLDB	8.5258582e-05
2,841	AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data	2022	VLDB	8.0637668e-05
4,827	PrivLava: Synthesizing Relational Data with Foreign Keys under Differential Privacy	2023	SIGMOD	6.4895329e-05

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