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In June 2016, Apple announced that it will deploy differential privacy forsome user data collection in order to ensure privacy of user data, even fromApple. The details of Apple's approach remained sparse. Although severalpatents have since appeared hinting at the algorithms that may be used toachieve differential privacy, they did not include a precise explanation of theapproach taken to privacy parameter choice. Such choice and the overallapproach to privacy budget use and management are key questions forunderstanding the privacy protections provided by any deployment ofdifferential privacy.  In this work, through a combination of experiments, static and dynamic codeanalysis of macOS Sierra (Version 10.12) implementation, we shed light on thechoices Apple made for privacy budget management. We discover and describeApple's set-up for differentially private data processing, including theoverall data pipeline, the parameters used for differentially privateperturbation of each piece of data, and the frequency with which such data issent to Apple's servers.  We find that although Apple's deployment ensures that the (differential)privacy loss per each datum submitted to its servers is $1$ or $2$, the overallprivacy loss permitted by the system is significantly higher, as high as $16$per day for the four initially announced applications of Emojis, New words,Deeplinks and Lookup Hints. Furthermore, Apple renews the privacy budgetavailable every day, which leads to a possible privacy loss of 16 times thenumber of days since user opt-in to differentially private data collection forthose four applications.  We advocate that in order to claim the full benefits of differentiallyprivate data collection, Apple must give full transparency of itsimplementation, enable user choice in areas related to privacy loss, and setmeaningful defaults on the privacy loss permitted.

Privacy Loss in Apple's Implementation of Differential Privacy on MacOS 10.12