Privacy Preserving Distributed Permutation Test
Yunlong Mao, Yuan Zhang · 2016
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.