Uniformity Testing in the Shuffle Model: Simpler, Better, Faster [article]

Clément L. Canonne, Hongyi Lyu
2021 arXiv   pre-print
Uniformity testing, or testing whether independent observations are uniformly distributed, is the prototypical question in distribution testing. Over the past years, a line of work has been focusing on uniformity testing under privacy constraints on the data, and obtained private and data-efficient algorithms under various privacy models such as central differential privacy (DP), local privacy (LDP), pan-privacy, and, very recently, the shuffle model of differential privacy. In this work, we
more » ... siderably simplify the analysis of the known uniformity testing algorithm in the shuffle model, and, using a recent result on "privacy amplification via shuffling," provide an alternative algorithm attaining the same guarantees with an elementary and streamlined argument.
arXiv:2108.08987v2 fatcat:mzarcifg3fevrb2672337bftbq