互动环境中的私人联合统计

论文标题

互动环境中的私人联合统计

Private Federated Statistics in an Interactive Setting

论文作者

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

论文摘要

设备上事件的私人学习统计数据可以改善用户体验。对于此类问题而言，私人算法可以从互动性中受益匪浅。我们认为，汇总协议可以启用交互式的私人联合统计系统，在该系统中，用户的设备可以保持对隐私保证的控制。我们描述了这种系统的体系结构，并分析其安全属性。

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.

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