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A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census
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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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Cited by 1 Pith paper
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Towards Better Attribute Inference Vulnerability Measures
A precision-recall composite measure with an original-data baseline labels over 25% of attacks on weakly anonymized microdata as at risk that the prior accuracy-only approach called safe.
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