Differential privacy is a recent notion of privacy tailored to the problem of statistical disclosure control: how to release statistical information about a set of people without compromising the the privacy of any individual.
We describe new work that extends differentially private data analysis beyond the traditional setting of a trusted curator operating, in perfect isolation, on a static dataset. We ask
|Published in||Symposium on Discrete Algorithms (SODA)|
|Publisher||Society for Industrial and Applied Mathematics|
Copyright © 2007 by Society for Industrial and Applied Mathematics.