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相关论文: Differential Privacy in the 2020 Decennial Census …

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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

When the U.S. Census Bureau announced its intention to modernize its disclosure avoidance procedures for the 2020 Census, it sparked a controversy that is still underway. The move to differential privacy introduced technical and procedural…

计算机与社会 · 计算机科学 2026-02-26 danah boyd , Jayshree Sarathy

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

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 concept of differential privacy (DP) has gained substantial attention in recent years, most notably since the U.S. Census Bureau announced the adoption of the concept for its 2020 Decennial Census. However, despite its attractive…

统计方法学 · 统计学 2024-08-14 Jörg Drechsler , James Bailie

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

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

In the face of increasingly severe privacy threats in the era of data and AI, the US Census Bureau has recently adopted differential privacy, the de facto standard of privacy protection for the 2020 Census release. Enforcing differential…

计算机与社会 · 计算机科学 2023-05-16 Keyu Zhu , Nabeel Gillani , Pascal Van Hentenryck

In a technical treatment, this article establishes the necessity of transparent privacy for drawing unbiased statistical inference for a wide range of scientific questions. Transparency is a distinct feature enjoyed by differential privacy:…

统计方法学 · 统计学 2022-09-20 Ruobin Gong

Agencies, such as the U.S. Census Bureau, release data sets and statistics about groups of individuals that are used as input to a number of critical decision processes. To conform to privacy and confidentiality requirements, these agencies…

人工智能 · 计算机科学 2024-11-26 Ferdinando Fioretto , Cuong Tran , Pascal Van Hentenryck

The U.S. Census Bureau collects and publishes detailed demographic data about Americans which are heavily used by researchers and policymakers. The Bureau has recently adopted the framework of differential privacy in an effort to improve…

计算机与社会 · 计算机科学 2023-12-11 Cory McCartan , Tyler Simko , Kosuke Imai

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

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

When differential privacy was created more than a decade ago, the motivating example was statistics published by an official statistics agency. In attempting to transition differential privacy from the academy to practice, the U.S. Census…

密码学与安全 · 计算机科学 2018-09-10 Simson L. Garfinkel , John M. Abowd , Sarah Powazek

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…

The US Decennial Census provides valuable data for both research and policy purposes. Census data are subject to a variety of disclosure avoidance techniques prior to release in order to preserve respondent confidentiality. While many are…

计算机与社会 · 计算机科学 2025-10-02 Cynthia Dwork , Kristjan Greenewald , Manish Raghavan

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…

Government agencies typically need to take potential risks of disclosure into account whenever they publish statistics based on their data or give external researchers access to collected data. In this context, the promise of formal privacy…

密码学与安全 · 计算机科学 2023-04-04 Joerg Drechsler

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…

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