Privacy Preserving Distributed Permutation Test

Yunlong Mao, Yuan Zhang
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Abstract

In this paper, we propose a privacy-preserving algorithm for two-party distributed permutation test for the difference of means. Our algorithm allows two parties to jointly perform a permutation test on the union of their data without revealing their data to each other. Our algorithm is useful especially in areas where the testing data often contains private information e.g. clinic trial and biomedical research. We have proved the security of our algorithm and used experiment to show its efficiency. To the best of our knowledge, we are the first to address the privacy issues in permutation tests.
保护隐私的分布式排列检验
本文提出了一种用于均值之差的两方分布排列检验的隐私保护算法。我们的算法允许双方在不向对方透露数据的情况下,共同对其数据的并集执行排列测试。我们的算法特别适用于测试数据通常包含私人信息的领域,例如临床试验和生物医学研究。我们证明了算法的安全性,并通过实验证明了算法的有效性。据我们所知,我们是第一个解决排列测试中的隐私问题的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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