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Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics

Summary: Releases linked employer-employee tabulations under provable privacy using Pufferfish-based, ER-EE-specific definitions. Census Bureau data experiments show utility at epsilon ≥ 1 comparable to or better than SDL for many queries, though some complex queries remain challenging. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5368
Venue
SIGMOD
Year
2017
Pagerank
6.465615e-05
Overall Rank
4,881 | 66.52%
DOI
10.1145/3035918.3035940

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{haney_sigmod17,
        title = {{Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics}},
        author = {Haney, Samuel and Machanavajjhala, Ashwin and Abowd, John M. and Graham, Matthew and Kutzbach, Mark and Vilhuber, Lars},
        series = {{SIGMOD} '17},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3035918.3035940},
        url = {https://dl.acm.org/doi/10.1145/3035918.3035940},
        year = {2017}
}

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