Differential Privacy in the 2020 Decennial Census and the Implications for Available Data Products

D. Boyd
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引用次数: 4

Abstract

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 avoidance. The confidentiality of individuals represented “anonymously” in these statistical tables will be protected by a “formal privacy” technique that allows the Bureau to mathematically assess the risk of revealing information about individuals in the released statistical tables. The Bureau’s approach is an implementation of “differential privacy,” and it gives a rigorously demonstrated guaranteed level of privacy protection that traditional methods of disclosure avoidance do not. Given the importance of the Census Bureau’s statistical tables to democracy, resource allocation, justice, and research, confusion about what differential privacy is and how it might alter or eliminate data products has rippled through the community of its data users, namely: demographers, statisticians, and census advocates. The purpose of this primer is to provide context to the Census Bureau’s decision to use a technique based on differential privacy and to help data users and other census advocates who are struggling to understand what this mathematical tool is, why it matters, and how it will affect the Bureau’s data products.
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2020年十年一次人口普查中的差异隐私及其对可用数据产品的影响
2021年初,美国人口普查局将开始根据2020年进行的十年一次的人口普查发布统计表。由于数据环境的重大变化,人口普查局正在改变其避免披露的方法。这些统计表中“匿名”个人的机密性将受到“正式隐私”技术的保护,该技术使统计局能够以数学方式评估公布的统计表中个人信息泄露的风险。该局的方法是“差别隐私”的实施,它提供了严格证明的有保障的隐私保护水平,这是传统的避免披露方法所没有的。鉴于人口普查局的统计表对民主、资源分配、正义和研究的重要性,关于什么是差别隐私以及它可能如何改变或消除数据产品的困惑已经在其数据用户社区中蔓延开来,即:人口统计学家、统计学家和人口普查倡导者。这本入门书的目的是为人口普查局决定使用基于差异隐私的技术提供背景,并帮助数据用户和其他人口普查倡导者,他们正在努力理解这个数学工具是什么,它为什么重要,以及它将如何影响人口普查局的数据产品。
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