Bayesian Differential Privacy on Correlated Data

Summary: Proposes Bayesian differential privacy (Pufferfish) for perturbation privacy on correlated data. Gaussian correlation model analyzes privacy across adversaries with varying priors, showing worst privacy under minimal knowledge and uncertain priors. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: hf3a598cbdf97293a
Venue: SIGMOD
Year: 2015
Pagerank: 7.6196809e-05
Overall Rank: 3,125 | 79.00%
DOI: 10.1145/2733272.2747643

Incoming Non-self Citations Over Time

Authors

1. Bin Yang (Rakuten, Inc.)
2. Issei Sato (University of Tokyo)
3. Hiroshi Nakagawa (University of Tokyo)

BibTeX Citation

@inproceedings{yang_sigmod15,
        title = {{Bayesian Differential Privacy on Correlated Data}},
        author = {Yang, Bin and Sato, Issei and Nakagawa, Hiroshi},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2733272.2747643},
        url = {https://dl.acm.org/doi/10.1145/2733272.2747643},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,911	Pufferfish Privacy Mechanisms for Correlated Data	2017	SIGMOD	6.9280385e-05
5,003	Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics	2017	SIGMOD	6.3175519e-05
6,036	Differentially Private Binary- and Matrix-Valued Data Query: An XOR Mechanism	2021	VLDB	5.9064579e-05
10,835	Composition for Pufferfish Privacy	2026	VLDB	4.9769913e-05
11,358	Balancing Privacy and Utility in Correlated Data: A Study of Bayesian Differential Privacy	2025	VLDB	4.9769913e-05
12,254	ConTPL: Controlling Temporal Privacy Leakage in Differentially Private Continuous Data Release	2018	VLDB	4.9769913e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
122	Revealing Information while Preserving Privacy	2003	PODS	0.00030756232
226	Limiting Privacy Breaches in Privacy Preserving Data Mining	2003	PODS	0.00023973554
520	Practical Privacy: The SuLQ Framework	2005	PODS	0.00016931295
879	Relationship Privacy: Output Perturbation for Queries with Joins	2009	PODS	0.00013293341
1,109	A Formal Analysis of Information Disclosure in Data Exchange	2004	SIGMOD	0.00011981617
1,156	PrivBayes: Private Data Release via Bayesian Networks	2014	SIGMOD	0.00011772019
1,250	No Free Lunch in Data Privacy	2011	SIGMOD	0.00011341376
1,782	The Boundary Between Privacy and Utility in Data Publishing	2007	VLDB	9.6477589e-05
2,299	Attacks on Privacy and deFinetti's Theorem	2009	SIGMOD	8.6748168e-05
2,371	Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies	2014	SIGMOD	8.5575829e-05
2,450	Simulatable Auditing	2005	PODS	8.4450717e-05
4,041	Epistemic Privacy	2008	PODS	6.8354934e-05
4,420	Towards an Axiomatization of Statistical Privacy and Utility	2010	PODS	6.6042887e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	10,550	A General Framework for Per-record Differential Privacy	2026	SIGMOD
2	1,889	Marginal Release Under Local Differential Privacy	2018	SIGMOD
3	2,371	Blowfish Privacy: Tuning Privacy-Utility Trade-offs using Policies	2014	SIGMOD
4	8,005	Quantifying identifiability to choose and audit epsilon in differentially private deep learning	2021	VLDB
5	1,156	PrivBayes: Private Data Release via Bayesian Networks	2014	SIGMOD
6	6,566	Differential Privacy in Data Publication and Analysis	2012	SIGMOD
7	10,650	Enhancing Local Differential Privacy Accuracy by Exploiting Inherent Uncertainty	2026	SIGMOD
8	10,835	Composition for Pufferfish Privacy	2026	VLDB
9	3,911	Pufferfish Privacy Mechanisms for Correlated Data	2017	SIGMOD
10	11,358	Balancing Privacy and Utility in Correlated Data: A Study of Bayesian Differential Privacy	2025	VLDB