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This article describes the disclosure avoidance algorithm that the U.S. Census Bureau used to protect the Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) of the 2020 Census. The tabulations contain statistics…

This article describes SafeTab-H, a disclosure avoidance algorithm applied to the release of the U.S. Census Bureau's Detailed Demographic and Housing Characteristics File B (Detailed DHC-B) as part of the 2020 Census. The tabulations…

This article describes a proposed differentially private (DP) algorithms that the US Census Bureau is considering to release the Detailed Demographic and Housing Characteristics (DHC) Race & Ethnicity tabulations as part of the 2020 Census.…

密码学与安全 · 计算机科学 2021-07-23 Sam Haney , William Sexton , Ashwin Machanavajjhala , Michael Hay , Gerome Miklau

In "The 2020 Census Disclosure Avoidance System TopDown Algorithm," Abowd et al. (2022) describe the concepts and methods used by the Disclosure Avoidance System (DAS) to produce formally private output in support of the 2020 Census…

密码学与安全 · 计算机科学 2025-08-12 Ryan Cumings-Menon , Robert Ashmead , Daniel Kifer , Philip Leclerc , Matthew Spence , Pavel Zhuravlev , John M. Abowd

In early 2021, the US Census Bureau will begin releasing statistical tables based on the decennial census conducted in 2020. Because of significant changes in the data landscape, the Census Bureau is changing its approach to disclosure…

计算机与社会 · 计算机科学 2019-07-09 danah boyd

In an era where external data and computational capabilities far exceed statistical agencies' own resources and capabilities, they face the renewed challenge of protecting the confidentiality of underlying microdata when publishing…

应用统计 · 统计学 2022-12-29 John M Abowd , Michael B Hawes

The Census TopDown Algorithm (TDA) is a disclosure avoidance system using differential privacy for privacy-loss accounting. The algorithm ingests the final, edited version of the 2020 Census data and the final tabulation geographic…

The U.S. Decennial Census serves as the foundation for many high-profile policy decision-making processes, including federal funding allocation and redistricting. In 2020, the Census Bureau adopted differential privacy to protect the…

密码学与安全 · 计算机科学 2026-04-21 Buxin Su , Weijie J. Su , Chendi Wang

The U.S. Census Bureau is using differential privacy (DP) to protect confidential respondent data collected for the 2020 Decennial Census of Population & Housing. The Census Bureau's DP system is implemented in the Disclosure Avoidance…

密码学与安全 · 计算机科学 2020-09-09 Simson L. Garfinkel , Philip Leclerc

As the U.S. Census Bureau implements its controversial new disclosure avoidance system, researchers and policymakers debate the necessity of new privacy protections for public statistics. With experiments on both public statistics and…

计算机与社会 · 计算机科学 2025-08-22 Ryan Steed , Diana Qing , Zhiwei Steven Wu

The US Census Bureau plans to protect the privacy of 2020 Census respondents through its Disclosure Avoidance System (DAS), which attempts to achieve differential privacy guarantees by adding noise to the Census microdata. By applying…

To protect the confidentiality of the 2020 Census, the U.S. Census Bureau adopted a statistical disclosure limitation framework based on the principles of differential privacy. A key component was the TopDown Algorithm, which applied…

统计方法学 · 统计学 2025-03-26 Robert Ashmead , Michael B. Hawes , Mary Pritts , Pavel Zhuravlev , Sallie Ann Keller

In 2017, the United States Census Bureau announced that because of high disclosure risk in the methodology (data swapping) used to produce tabular data for the 2010 census, a different protection mechanism based on differential privacy…

数据库 · 计算机科学 2024-07-24 Krish Muralidhar , Steven Ruggles

The 2020 Decennial Census will be released with a new disclosure avoidance system in place, putting differential privacy in the spotlight for a wide range of data users. We consider several key applications of Census data in redistricting,…

计算机与社会 · 计算机科学 2022-03-11 Aloni Cohen , Moon Duchin , JN Matthews , Bhushan Suwal

We propose Bayesian methods to assess the statistical disclosure risk of data released under zero-concentrated differential privacy, focusing on settings with a strong hierarchical structure and categorical variables with many levels. Risk…

统计方法学 · 统计学 2023-02-01 Zeki Kazan , Jerome Reiter

This paper is motivated by applications of a Census Bureau interested in releasing aggregate socio-economic data about a large population without revealing sensitive information about any individual. The released information can be the…

数据库 · 计算机科学 2021-05-11 Ferdinando Fioretto , Pascal Van Hentenryck , Keyu Zhu

The US Census Bureau will implement a new privacy-preserving disclosure avoidance system (DAS), which includes application of differential privacy, on the public-release 2020 census data. There are concerns that the DAS may bias small-area…

Protecting an individual's privacy when releasing their data is inherently an exercise in relativity, regardless of how privacy is qualified or quantified. This is because we can only limit the gain in information about an individual…

密码学与安全 · 计算机科学 2026-02-26 James Bailie , Ruobin Gong , Xiao-Li Meng

Data from the Decennial Census is published only after applying a disclosure avoidance system (DAS). Data users were shaken by the adoption of differential privacy in the 2020 DAS, a radical departure from past methods. The goal of this…

计算机与社会 · 计算机科学 2026-02-23 Christian Cianfarani , Aloni Cohen

The US Census Bureau Disclosure Avoidance System (DAS) balances confidentiality and utility requirements for the decennial US Census (Abowd et al., 2022). The DAS was used in the 2020 Census to produce demographic datasets critically used…

机器学习 · 计算机科学 2026-03-12 Badih Ghazi , Pritish Kamath , Ravi Kumar , Pasin Manurangsi , Adam Sealfon
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