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Towards Confidentiality-strengthened Personalized Genomic Medicine Embedding Homomorphic Cryptography

机译:朝着保密 - 加强的个性化基因组医学嵌入均匀密码学

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In this paper, we analyze and propose a solution for the challenges that come with personalized genomic and, most importantly, of performing queries on sequenced dataset sitting on a cloud server. This work provides scenarios for its application in personalized genomic medicine, and tests homomorphic encryption technique to assist in improving the strength of their privacy at non-prohibitive performance cost. By experimental testing using HElib, we make a first step towards performing practical computation over the relevant portions of the genomic dataset of an individual for a first round of practical diagnosis rules.
机译:在本文中,我们分析并提出了个性化基因组的挑战的解决方案,并且最重要的是在坐在云服务器上坐在云服务器上进行测序的数据集进行查询。这项工作为其在个性化基因组中的应用提供了方案,并测试了同性恋加密技术,以协助提高他们在非禁止性能成本上的隐私强度。通过使用赫布的实验测试,我们为第一轮实际诊断规则进行了对个人基因组数据集的相关部分进行实际计算的第一步。

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