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Privacy-Preserving Whole-Genome Variant Queries

机译：保护隐私的全基因组变异查询

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Medical research and treatments rely increasingly on genomic data. Queries on so-called variants are of high importance in, e.g., biomarker identification and general disease association studies. However, the human genome is a very sensitive piece of information that is worth protecting. By observing queries and responses to classical genomic databases, medical conditions can be inferred. The Beacon project is an example of a public genomic querying service, which undermines the privacy of the querier as well as individuals in the database. By secure outsourcing via secure multi-party computation (SMPC), we enable privacy-preserving genomic database queries that protect sensitive data contained in the queries and their respective responses. At the same time, we allow for multiple genomic databases to combine their datasets to achieve a much larger search space, without revealing the actual databases' contents to third parties. SMPC is generic and allows to apply further processing like aggregation to query results. We measure the performance of our approach for realistic parameters and achieve convincingly fast runtimes that render our protocol applicable to real-world medical data integration settings. Our prototype implementation can process a private query with 5 genetic variant conditions against a person's exome with 100,000 genomic variants in less than 180 ms online runtime, including additional range and equality checks for auxiliary data.
机译：医学研究和治疗越来越依赖基因组数据。对所谓变体的查询在例如生物标志物鉴定和一般疾病关联研究中非常重要。但是，人类基因组是非常敏感的信息，值得保护。通过观察对经典基因组数据库的查询和响应，可以推断出医疗状况。 Beacon项目是公共基因组查询服务的一个示例，该服务破坏了查询者以及数据库中个人的隐私。通过安全多方计算（SMPC）进行的安全外包，我们实现了保护隐私的基因组数据库查询，从而保护了查询中包含的敏感数据及其各自的响应。同时，我们允许多个基因组数据库组合其数据集以实现更大的搜索空间，而无需向第三方透露实际数据库的内容。 SMPC是通用的，允许对聚合结果进行进一步的处理，例如聚合。我们测量逼真的参数方法的性能，并获得令人信服的快速运行时间，这些运行时间使我们的协议适用于实际医疗数据集成设置。我们的原型实现可以在不到180毫秒的在线运行时间中，针对具有100,000个基因组变异的人的外显子组，对具有5个遗传变异条件的私人查询进行处理，包括对辅助数据进行额外的范围和相等性检查。

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