Stronger Privacy Amplification by Shuffling for Renyi and Approximate Differential Privacy
Vitaly Feldman, Audra McMillan, Kunal Talwar · Society for Industrial and Applied Mathematics eBooks · 2023
The shuffle model of differential privacy has gained significant interest as an intermediate trust model between the standard local and central models [18, 12]. A key result in this model is that randomly shuffling locally randomized data amplifies differential privacy guarantees. Such amplification implies substantially stronger privacy guarantees for systems in which data is contributed anonymously [8].