Balancing Privacy and Utility in Correlated Data: A Study of Bayesian Differential Privacy
Summary: Derives practical utility guarantees for Bayesian differential privacy (BDP) under arbitrary and structured correlations (Gaussian multivariate, Markov chains) and formalizes theoretical links to standard DP. Proposes a method to adapt DP mechanisms to meet BDP with competitive utility, validated on real datasets. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Martin Lange (Karlsruhe Institute of Technology)
- 2. Patricia Guerra-Balboa (Karlsruhe Institute of Technology)
- 3. Javier Parra-Arnau (Universitat Politècnica de Catalunya)
- 4. Thorsten Strufe (Karlsruhe Institute of Technology)
BibTeX Citation
@article{lange_vldb25,
title = {{Balancing Privacy and Utility in Correlated Data: A Study of Bayesian Differential Privacy}},
author = {Lange, Martin and Guerra-Balboa, Patricia and Parra-Arnau, Javier and Strufe, Thorsten},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {11},
pages = {4090--4103},
doi = {10.14778/3749646.3749679},
url = {https://doi.org/10.14778/3749646.3749679},
year = {2025}
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Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,230 | No Free Lunch in Data Privacy | 2011 | SIGMOD | 0.00011572271 |
| 2,562 | Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies | 2014 | SIGMOD | 8.4127196e-05 |
| 3,375 | Bayesian Differential Privacy on Correlated Data | 2015 | SIGMOD | 7.4639817e-05 |
| 4,302 | Pufferfish Privacy Mechanisms for Correlated Data | 2017 | SIGMOD | 6.7720437e-05 |
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