Cybersecurity Policy Report, NIST Finalizes Guidance on Differential Privacy Techniques, (Mar 7, 2025)

By Tony Foley

The National Institute of Standards and Technology (NIST) yesterday finalized its guidance on evaluating the use of differential privacy techniques to protect sensitive personal data contained in large datasets.

Proposed originally in December 2023 (CPR, Dec. 11, 2023), the guidance (NIST SP 800-22, Guidelines for Evaluating Differential Privacy Guarantees) describes differential privacy as a mathematical framework that quantifies privacy loss to entities when their data appears in a large data set. The goal of the publication is to help practitioners better understand how to think about differentially private software solutions. Multiple factors for consideration are provided 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.

The finalized guidance sets forth an introduction in part 1, and is then divided into the following three substantive parts:

1. Part 2, in which NIST defines and explains the concept of differential privacy, discusses how to reason about and compare differential privacy guarantees, describes how a differential privacy guarantee can impact real-world outcomes, and highlights the potential hazards in defining and evaluating such guarantees;

2. Part 3, which outlines the composition of algorithms that achieve differential privacy, discusses the trade-offs between privacy and data utility inherent in the use of differential privacy techniques; and

3. Part 4, which reviews the practical concerns in deploying differentially private analysis techniques, including the threat model, which describes who can be considered trustworthy and who should be considered malicious, as well as challenges in implementation and security concerns.

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