Personalized Privacy Amplification via Importance Sampling

arXiv:2307.10187v2 Announce Type: replace-cross
Abstract: We examine the privacy-enhancing properties of importance sampling. In importance sampling, selection probabilities are heterogeneous and each selected data point is weighted by the reciprocal of its selection probability. Due to the heterogeneity of importance sampling, we express our results within the framework of personalized differential privacy. We first consider the general case where an arbitrary personalized differentially private mechanism is subsampled with an arbitrary importance sampling distribution and show that the resulting mechanism also …

abstract arxiv cs.cr cs.lg data differential differential privacy express framework importance personalized privacy probability sampling stat.ml type via