The US National Institute of Standards and Technology (NIST) has published its finalised Guidelines for Evaluating ‘Differential Privacy’ Guarantees to De-Identify Data (NIST Special Publication 800-226). Differential privacy works by adding random “noise” to the data in a way that obscures the identity of the individuals but keeps the database useful overall as a source of statistical information. However, noise applied in the wrong way can jeopardise privacy or render the data less useful. These guidelines aim 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.
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