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  • Is differential privacy a naive tool?

    Here, differential privacy pro-vides an obvious tool. For small values of , because exp( ) ≈ (1 + ), and so as discussed earlier, a simple (but possibly naive) first cut at a model is to view each agent as having some linear cost for participating in a private study.

  • What happened to Apple's 'diferential privacy' on macOS 10?

    Privacy Loss in Apple’s Implementation of Diferential Privacy on MacOS 10.12 In June 2016, Apple made a bold announcement that it will deploy local diferential privacy for some of their user data collection in order to ensure privacy of user data, even from Apple [21, 23]. The details of Apple’s approach remained sparse.

  • What is local differential privacy?

    Local differential privacy has the advantage that the data is randomized before being sent from the device, so the server never sees or receives raw data. Our system is designed to be opt-in and transparent. No data is recorded or transmitted before the user explicitly chooses to report usage information.

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