IACR News item: 16 July 2015
Sébastien Canard, Baptiste Olivier
ePrint ReportUsing differential privacy \\emph{in distribution}, we then give simple conditions for an instance-based noise mechanism to be (\\epsilon,\\delta)-differentially private. After that, we exploit these conditions to design a new (\\epsilon,\\delta)-differentially private instance-based noise algorithm. Compare to existing ones, our algorithm have a better accuracy when used to answer a query in a differentially private manner.
In particular, our algorithm does not require the computation of the so-called Smooth Sensitivity, usually used in instance-based noise algorithms, and which was proved to be NP hard to compute in some cases, namely statistics queries on some graphs. Our algorithm handles such situations and in particular some cases for which no instance-based noise mechanism were known to perform well.
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