On the Power of Multiple Anonymous Messages

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On the Power of Multiple Anonymous Messages

29 August 2019

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Papers citing "On the Power of Multiple Anonymous Messages"

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Title
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities Tal Wagner FedML 94 0 0 21 Feb 2025
Privacy Enhancement via Dummy Points in the Shuffle Model Xiaochen Li Weiran Liu Hanwen Feng Kunzhe Huang Jinfei Liu K. Ren Zhan Qin FedML 100 4 0 29 Sep 2020
Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Shuang Song Kunal Talwar Abhradeep Thakurta 82 84 0 10 Jan 2020
Separating Local & Shuffled Differential Privacy via Histograms Victor Balcer Albert Cheu FedML 137 68 0 15 Nov 2019
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 116 57 0 24 Sep 2019
Improving Utility and Security of the Shuffler-based Differential Privacy Tianhao Wang Bolin Ding Min Xu Zhicong Huang Cheng Hong Jingren Zhou Ninghui Li S. Jha 147 11 0 30 Aug 2019