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

• URL: http://arxiv.org/abs/2312.11283v3
• Date: Mon, 28 Jul 2025 11:10:54 GMT
• Title: A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census
• Authors: 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,
• Abstract summary: We show that individual, confidential microdata records from the 2010 U.S. Census can be accurately reconstructed.<n>Ninety-seven million person records (every resident in 70% of all census blocks) are exactly reconstructed with provable certainty using only public information.<n>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.
• Score: 6.851716728384597
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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