HackerPapers

arXiv:2312.11283stat.AP

A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census

John M. Abowd, Tamara Adams, Robert Ashmead, David Darais, Sourya Dey, Simson L. Garfinkel, Nathan Goldschlag, Michael B. Hawes, Daniel Kifer, Philip Leclerc, Ethan Lew, Scott Moore, Rolando A. Rodríguez, Ramy N. Tadros, Lars Vilhuber

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

We show that individual, confidential microdata records from the 2010 U.S. Census of Population and Housing can be accurately reconstructed from the published tabular summaries. Ninety-seven million person records (every resident in 70% of all census blocks) are exactly reconstructed with provable certainty using only public information. We further show that a hypothetical attacker using our methods can reidentify with 95% accuracy population unique individuals who are perfectly reconstructed and not in the modal race and ethnicity category in their census block (3.4 million persons)--a result that is only possible because their confidential records were used in the published tabulations. Finally, we show that the methods used for the 2020 Census, based on a differential privacy framework, provide better protection against this type of attack, with better published data accuracy, than feasible alternatives.

arXiv comments
This is the accepted Harvard Data Science Review (2025) paper. The accepted supplemental text is here: https://arxiv.org/abs/2312.11283v2
Journal reference
DOI
doi:10.1162/99608f92.4a1ebf70
Subjects
stat.APApplications (Statistics) cs.CRCryptography and Security econ.EMEconometrics

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Jul 2026 to Jul 2026. Found in 2 HN submissions from Dec 2023 to Dec 2023. Open submission discussions.

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  1. An American Privacy Emergency 1 comment
    • (1) "A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census" https://arxiv.org/pdf/2312.11283 (2) By adding carefully tuned Gaussian noise. In the last 6 years we have also figured out how to add much less Gaussian noise: "The 2020 Census Disclosure…

      flowercalledView on HNParent context

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