Explaining Differentially Private Query Results With DPXPlain
Summary: DPXPlain: first system to explain group-by aggregate query anomalies under Differential Privacy, letting users validity-check comparisons between two groups. Produces a DP-guaranteed interactive explanation table of approximate top-k predicate explanations with relative influences and confidence-interval ranks. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Tingyu Wang (Duke University)
- 2. Yuchao Tao (Duke University)
- 3. Amir Gilad (Hebrew University)
- 4. Ashwin Machanavajjhala (Duke University)
- 5. Sudeepa Roy (Duke University)
BibTeX Citation
@article{wang_vldb23,
title = {{Explaining Differentially Private Query Results With DPXPlain}},
author = {Wang, Tingyu and Tao, Yuchao and Gilad, Amir and Machanavajjhala, Ashwin and Roy, Sudeepa},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {12},
pages = {3962--3965},
doi = {10.14778/3611540.3611596},
url = {https://doi.org/10.14778/3611540.3611596},
year = {2023}
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 191 | Scorpion: Explaining Away Outliers in Aggregate Queries | 2013 | VLDB | 0.00026096009 |
| 663 | A Formal Approach to Finding Explanations for Database Queries | 2014 | SIGMOD | 0.00015174751 |
| 858 | Interpretable and Informative Explanations of Outcomes | 2015 | VLDB | 0.0001356511 |
| 1,144 | PrivateSQL: A Differentially Private SQL Query Engine | 2019 | VLDB | 0.00011999046 |
| 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 |
| 8,719 | DPXPlain: Privately Explaining Aggregate Query Answers | 2023 | VLDB | 5.3774243e-05 |
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