Differential Privacy and Federal Data Releases

Author:

Reiter Jerome P.1

Affiliation:

1. Department of Statistical Science, Duke University, Durham, North Carolina 27705, USA;

Abstract

Federal statistics agencies strive to release data products that are informative for many purposes, yet also protect the privacy and confidentiality of data subjects’ identities and sensitive attributes. This article reviews the role that differential privacy, a disclosure risk criterion developed in the cryptography community, can and does play in federal data releases. The article describes potential benefits and limitations of using differential privacy for federal data, reviews current federal data products that satisfy differential privacy, and outlines research needed for adoption of differential privacy to become widespread among federal agencies.

Publisher

Annual Reviews

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A data-driven approach to choosing privacy parameters for clinical trial data sharing under differential privacy;Journal of the American Medical Informatics Association;2024-03-08

2. Differential Privacy for Government Agencies—Are We There Yet?;Journal of the American Statistical Association;2023-01-02

3. OUP accepted manuscript;Journal of Survey Statistics and Methodology;2022

4. Suppression criteria for inaccurate estimates;Statistical Journal of the IAOS;2021-11-26

5. Effects of differential privacy techniques: Considerations for end users;Research in Social and Administrative Pharmacy;2021-05

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