Article

A Re-examination of the Census Bureau Reconstruction and Reidentification Attack

Author:

Krishnamurty MuralidharAuthors Info & Claims

Privacy in Statistical Databases: International Conference, PSD 2022, Paris, France, September 21–23, 2022, Proceedings

Pages 312 - 323

https://doi.org/10.1007/978-3-031-13945-1_22

Published: 21 September 2022 Publication History

Abstract

Recent analysis by researchers at the U.S. Census Bureau claims that by reconstructing the tabular data released from the 2010 Census, it is possible to reconstruct the original data and, using an accurate external data file with identity, reidentify 179 million respondents (approximately 58% of the population). This study shows that there are a practically infinite number of possible reconstructions, and each reconstruction leads to assigning a different identity to the respondents in the reconstructed data. The results reported by the Census Bureau researchers are based on just one of these infinite possible reconstructions and is easily refuted by an alternate reconstruction. Without definitive proof that the reconstruction is unique, or at the very least, that most reconstructions lead to the assignment of the same identity to the same respondent, claims of confirmed reidentification are highly suspect and easily refuted.

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Cited By

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Aghaddar MSu LSlokom MBarnhoorn Lde Wolf P(2024)A Case Study Exploring Data Synthesis Strategies on Tabular vs. Aggregated Data Sources for Official StatisticsPrivacy in Statistical Databases10.1007/978-3-031-69651-0_28(420-435)Online publication date: 25-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-69651-0_28
Sánchez DJebreel NMuralidhar KDomingo-Ferrer JBlanco-Justicia A(2024)An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census MicrodataPrivacy in Statistical Databases10.1007/978-3-031-69651-0_14(213-224)Online publication date: 25-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-69651-0_14

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Published In

Privacy in Statistical Databases: International Conference, PSD 2022, Paris, France, September 21–23, 2022, Proceedings

Sep 2022

374 pages

ISBN:978-3-031-13944-4

DOI:10.1007/978-3-031-13945-1

Editors:
Josep Domingo-Ferrer
Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
,
Maryline Laurent
Télécom SudParis, Palaiseau, France

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Springer-Verlag

Berlin, Heidelberg

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Published: 21 September 2022

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Aghaddar MSu LSlokom MBarnhoorn Lde Wolf P(2024)A Case Study Exploring Data Synthesis Strategies on Tabular vs. Aggregated Data Sources for Official StatisticsPrivacy in Statistical Databases10.1007/978-3-031-69651-0_28(420-435)Online publication date: 25-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-69651-0_28
Sánchez DJebreel NMuralidhar KDomingo-Ferrer JBlanco-Justicia A(2024)An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census MicrodataPrivacy in Statistical Databases10.1007/978-3-031-69651-0_14(213-224)Online publication date: 25-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-69651-0_14

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An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census Microdata

Escalation of Commitment: A Case Study of the United States Census Bureau Efforts to Implement Differential Privacy for the 2020 Decennial Census

Improving Algebraic Reconstruction Techniques with Nonlinear Iterating Algorithms

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