Private Federated Statistics in an Interactive Setting

Audra McMillan,Omid Javidbakht,Kunal Talwar, Elliot Briggs,Mike Chatzidakis,Junye Chen,John Duchi,Vitaly Feldman, Yusuf Goren, Michael Hesse,Vojta Jina, Anil Katti, Albert Liu, Cheney Lyford, Joey Meyer, Alex Palmer,David Park,Wonhee Park,Gianni Parsa, Paul Pelzl,Rehan Rishi,Congzheng Song, Shan Wang, Shundong Zhou

arxiv（2022）

引用 0|浏览50

暂无评分

摘要

Privately learning statistics of events on devices can enable improved user experience. Differentially private algorithms for such problems can benefit significantly from interactivity. We argue that an aggregation protocol can enable an interactive private federated statistics system where user's devices maintain control of the privacy assurance. We describe the architecture of such a system, and analyze its security properties.

查看译文

关键词

private federated statistics

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要