Distributed Differential Privacy via Shuffling vs Aggregation: a Curious Study

ePrint Report: Distributed Differential Privacy via Shuffling vs Aggregation: a Curious Study

Yu Wei, Jingyu Jia, Yuduo Wu, Changhui Hu, Changyu Dong, Zheli Liu, Xiaofeng Chen, Yun Peng, Shaowei Wang

How to achieve distributed differential privacy (DP) without a trusted central party is of great interest in both theory and practice. Recently, the shuffle model has attracted much attention. Unlike the local DP model in which the users send randomized data directly to the data collector/analyzer, in the shuffle model …

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