Privacy-MaxEnt: Integrating Background Knowledge in Privacy Quantification

Summary: Privacy-MaxEnt uses maximum entropy to quantify privacy in PPDP, modeling P(SA|QI) as unknowns constrained by background knowledge and published data. It yields the least-biased P(SA|QI) under all constraints, providing a principled privacy metric. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: hbf2dfd2cb7b1e999
Venue: SIGMOD
Year: 2008
Pagerank: 5.268646e-05
Overall Rank: 8,826 | 40.66%
DOI: 10.1145/1376616.1376665

Incoming Non-self Citations Over Time

Authors

1. Wenliang Du (Syracuse University)
2. Zhouxuan Teng (Syracuse University)
3. Zutao Zhu (Syracuse University)

BibTeX Citation

@inproceedings{du_sigmod08,
        title = {{Privacy-MaxEnt: Integrating Background Knowledge in Privacy Quantification}},
        author = {Du, Wenliang and Teng, Zhouxuan and Zhu, Zutao},
        series = {{SIGMOD} '08},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1376616.1376665},
        url = {https://dl.acm.org/doi/10.1145/1376616.1376665},
        year = {2008}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,296	Attacks on Privacy and deFinetti's Theorem	2009	SIGMOD	8.6789249e-05

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
13	Mining Association Rules between Sets of Items in Large Databases	1993	SIGMOD	0.00064420972
68	Privacy-Preserving Data Mining	2000	SIGMOD	0.00037958605
254	On the Design and Quantification of Privacy Preserving Data Mining Algorithms	2001	PODS	0.00023020039
469	Incognito: Efficient Full-Domain K-Anonymity	2005	SIGMOD	0.0001775622
584	Anatomy: Simple and Effective Privacy Preservation	2006	VLDB	0.00015954725
1,239	Maintaining Data Privacy in Association Rule Mining	2002	VLDB	0.00011384824
4,133	Privacy Skyline: Privacy with Multidimensional Adversarial Knowledge	2007	VLDB	6.7880955e-05

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