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首页> 外文会议>IEEE International symposium on computer-based medical systems >Privacy-Aware Genome Mining: Server-Assisted Protocols for Private Set Intersection and Pattern Matching
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Privacy-Aware Genome Mining: Server-Assisted Protocols for Private Set Intersection and Pattern Matching

机译：隐私感知的基因组挖掘：专用集交叉和模式匹配的服务器辅助协议

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摘要

The Human Genome Project has generated a great wealth of information. Currently, almost all human genome has been sequenced and now it is time to identify the functionality of each gene. The sequence of base pairs accounts for approximately 3 billion elements. While there are many efficient algorithms and implementations to mine this information, doing it privately is a great challenge. Current state-of-the-art methods have improved their efficiency, but they are not practical yet. In this article, we introduce several protocols to drastically boost the performance of genome mining processes while guaranteeing privacy, thus, enabling practical implementations. We describe how to solve the private set intersection problem and a set of pattern matching queries with privacy. The proposed protocols are server-assisted and we prove that they are secure under the semi-honest model. We report the assessment of our solution using synthetic datasets and prove their efficiency.
机译：人类基因组计划已经产生了大量的信息。目前，几乎所有人类基因组都已测序，现在是时候鉴定每个基因的功能了。碱基对的序列约占30亿个元素。尽管有许多有效的算法和实现可用于挖掘此信息，但私下处理它是一个巨大的挑战。当前最先进的方法提高了它们的效率，但是还不实用。在本文中，我们介绍了几种协议，可以在保证隐私的同时极大地提高基因组挖掘过程的性能，从而实现实际的实现。我们描述了如何解决私有集相交问题以及具有隐私的一组模式匹配查询。所提出的协议是服务器辅助的，我们证明了它们在半诚实模型下的安全性。我们使用综合数据集报告对我们解决方案的评估，并证明其效率。

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