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 [7]. We describe new work [10, 9] that extends differentially private data analysis beyond the traditional setting of a trusted curator operating, in perfect isolation, on a static dataset. We ask