Security

Differential Privacy Under Fire

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Executive Summary

Anonymizing private data before release is not enough to reliably protect privacy, as Netflix and AOL have learned to their cost. Recent research on differential privacy opens a way to obtain robust, provable privacy guarantees, and systems like PINQ and Airavat now offer convenient frameworks for processing arbitrary user-specified queries in a differentially private way. However, these systems are vulnerable to a variety of covert-channel attacks that can be exploited by an adversarial querier. The authors describe several different kinds of attacks, all feasible in PINQ and some in Airavat.

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