Counting Distinct Elements Under Person-Level Differential Privacy
Data Structures and Algorithms
2023-10-30 v3 Cryptography and Security
Abstract
We study the problem of counting the number of distinct elements in a dataset subject to the constraint of differential privacy. We consider the challenging setting of person-level DP (a.k.a. user-level DP) where each person may contribute an unbounded number of items and hence the sensitivity is unbounded. Our approach is to compute a bounded-sensitivity version of this query, which reduces to solving a max-flow problem. The sensitivity bound is optimized to balance the noise we must add to privatize the answer against the error of the approximation of the bounded-sensitivity query to the true number of unique elements.
Keywords
Cite
@article{arxiv.2308.12947,
title = {Counting Distinct Elements Under Person-Level Differential Privacy},
author = {Alexander Knop and Thomas Steinke},
journal= {arXiv preprint arXiv:2308.12947},
year = {2023}
}