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A Rigorous and Customizable Framework for Privacy

Summary: Pufferfish: a rigorous, customizable privacy framework enabling domain experts to specify secrets, discriminative pairs, and data-generation constraints to derive application-specific privacy definitions. Subsumes and clarifies differential privacy's independence assumption, generalizes composition, protects unbounded continuous/aggregate attributes, and accounts for prior releases. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1566
Venue
PODS
Year
2012
Pagerank
6.3969504e-05
Overall Rank
5,027 | 65.52%
DOI
10.1145/2213556.2213571

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kifer_pods12,
        address = {New York, NY, USA},
        series = {{PODS} '12},
        title = {{A Rigorous and Customizable Framework for Privacy}},
        url = {https://dl.acm.org/doi/10.1145/2213556.2213571},
        doi = {10.1145/2213556.2213571},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Kifer, Daniel and Machanavajjhala, Ashwin},
        year = {2012}
}

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