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2020-09-15 12:00:00 | Threat Models for Differential Privacy (lien direct) | This post is part of a series on differential privacy. Learn more and browse all the posts published to date on the differential privacy blog series page in NIST's Privacy Engineering Collaboration Space. It's not so simple to deploy a practical system that satisfies differential privacy. Our example in the last post was a simple Python program that adds Laplace noise to a function computed over the sensitive data. For this to work in practice, we'd need to collect all of the sensitive data on one server to run our program. What if that server gets hacked? Differential privacy provides no | Threat |
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