Issues Encountered Deploying Differential Privacy

Abstract

When differential privacy was created more than a decade ago, the motivating example was statistics published by an official statistics agency. In attempting to transition differential privacy from the academy to practice, the U.S. Census Bureau has encountered many challenges unanticipated by differential privacy's creators. These challenges include obtaining qualified personnel and a suitable computing environment, the difficulty accounting for all uses of the confidential data, the lack of release mechanisms that align with the needs of data users, the expectation on the part of data users that they will have access to micro-data, and the difficulty in setting the value of the privacy-loss parameter, $\epsilon$ (epsilon), and the lack of tools and trained individuals to verify the correctness of differential privacy implementations.

References in corpus (1)

• RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response

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• Generating Poisson-Distributed Differentially Private Synthetic Data
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