Differential Privacy Under Fire

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.

Provided by: University of Pennsylvania Topic: Security Date Added: Jun 2011 Format: PDF

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