Differential Privacy and Survey Sampling

Abstract

The Horvitz-Thompson estimate of a total can be seen as as differentially private mechanism applied to this population total. We provide forumlae to compute the $\hat{I}\mu$ and $\hat{I}´$ parameter for this specific mecanism, coupled or not coupled with the addition of a Laplace or a Gaussian noise. This allows to determine the scale of the Laplace privacy mechanism to be added to reach a specified level of privacy, expressed in terms of $\hat{I}\mu ,\hat{I}´$ differential privacy. In particular, we provide simple formulae for the special case of simple random sampling on binary data.