Ripple Mechanisms for Discrete and Private Statistics
Abstract
We study \emph{ripple mechanisms} for pure differentially private computation of discrete statistics. For each of three natural statistics -- sum, count, and vote -- we construct an efficient instance of the ripple mechanism and show that it is often more accurate than the previous state of the art. We also prove that ripple mechanisms are, in some settings, optimal among all discrete pure differentially private additive noise mechanisms.
