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Differential privacy provides a mathematical way to describe the privacy loss associated with using someone’s data. This guide helps practitioners assess what a differentially private software system promises and how those promises can change in practical use.
The authors organize their discussion around a privacy pyramid and common hazards in defining, evaluating and implementing guarantees. Examples address data analysis, sharing and the choices that affect the balance between privacy and utility. The complete original publication retains its diagrams, definitions, examples and references.
Joseph P. Near, David Darais, Naomi Lefkovitz and Gary S. Howarth (2025). Guidelines for Evaluating Differential Privacy Guarantees. National Institute of Standards and Technology. https://doi.org/10.6028/NIST.SP.800-226. Republished courtesy of the National Institute of Standards and Technology.