SplitX: high-performance private analytics

SIGCOMM, pp. 315-326, 2013.

Cited by: 62|Bibtex|Views4|DOI:https://doi.org/10.1145/2486001.2486013
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

There is a growing body of research on mechanisms for preserving online user privacy while still allowing aggregate queries over private user data. A common approach is to store user data at users' devices, and to query the data in such a way that a differentially private noisy result is produced without exposing individual user data to a...More

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