Hiding Among the Clones: A Simple and Nearly Optimal Analysis of Privacy Amplification by Shuffling

Recent work of Erlingsson, Feldman, Mironov, Raghunathan, Talwar, and Thakurta [1] demonstrates that random shuffling amplifies differential privacy guarantees of locally randomized data. Such amplification implies substan-tially stronger privacy guarantees for systems in which data is contributed anonymously [2] and has lead to significant interest in the shuffle model of privacy [3], [1]. We giv...