Near, J.
, Darais, D.
and Lefkovitz, N.
(2025),
Guidelines for Evaluating Differential Privacy Guarantees, Special Publication (NIST SP), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.SP.800-226, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=958909
(Accessed April 30, 2025)
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Guidelines for Evaluating Differential Privacy Guarantees
Published
Author(s)
Joseph Near, David Darais,
Abstract
This publication describes differential-privacy -- a mathematical framework that quantifies privacy loss to entities when their data appears in a dataset. It serves to fulfill one of the assignments to the National Institute of Standards and Technology (NIST) by the Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence issued on October 30, 2023. The primary goal of this publication is to help practitioners of all backgrounds better understand how to think about differentially private software solutions. Multiple factors for consideration are identified in a differential privacy pyramid along with several privacy hazards, which are common pitfalls that arise as the mathematical framework of differential privacy is realized in practice.Citation
Special Publication (NIST SP) - 800-226
Report Number
800-226
NIST Pub Series
Pub Type
NIST Pubs
Download Paper
Keywords
Anonymization, data analytics, data privacy, de-identification, differential privacy, privacy, privacy-enhancing technologies
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created March 6, 2025