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Secure searching of biomarkers through hybrid homomorphic encryption scheme

机译:通过混合同态加密方案安全搜索生物标记

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Background As genome sequencing technology develops rapidly, there has lately been an increasing need to keep genomic data secure even when stored in the cloud and still used for research. We are interested in designing a protocol for the secure outsourcing matching problem on encrypted data. Method We propose an efficient method to securely search a matching position with the query data and extract some information at the position. After decryption, only a small amount of comparisons with the query information should be performed in plaintext state. We apply this method to find a set of biomarkers in encrypted genomes. The important feature of our method is to encode a genomic database as a single element of polynomial ring. Result Since our method requires a single homomorphic multiplication of hybrid scheme for query computation, it has the advantage over the previous methods in parameter size, computation complexity, and communication cost. In particular, the extraction procedure not only prevents leakage of database information that has not been queried by user but also reduces the communication cost by half. We evaluate the performance of our method and verify that the computation on large-scale personal data can be securely and practically outsourced to a cloud environment during data analysis. It takes about 3.9 s to search-and-extract the reference and alternate sequences at the queried position in a database of size 4M. Conclusion Our solution for finding a set of biomarkers in DNA sequences shows the progress of cryptographic techniques in terms of their capability can support real-world genome data analysis in a cloud environment.
机译:背景技术随着基因组测序技术的飞速发展,近来,即使将基因组数据存储在云中并仍用于研究中,仍需要保持基因组数据安全。我们感兴趣的是为加密数据上的安全外包匹配问题设计协议。方法我们提出了一种有效的方法,用查询数据安全地搜索匹配位置并提取该位置的一些信息。解密后,只能在纯文本状态下执行与查询信息的少量比较。我们应用此方法在加密的基因组中找到一组生物标记。我们方法的重要特征是将基因组数据库编码为多项式环的单个元素。结果由于我们的方法需要使用混合方案的单同态乘法来进行查询计算,因此与以前的方法相比,它在参数大小,计算复杂度和通信成本方面具有优势。特别地,提取过程不仅防止了用户尚未查询的数据库信息的泄漏,而且将通信成本降低了一半。我们评估了该方法的性能,并验证了在数据分析过程中可以安全,实用地将对大规模个人数据的计算外包给云环境。在大小为4M的数据库中的查询位置搜索和提取参考序列和备用序列大约需要3.9 s。结论我们的用于在DNA序列中找到一组生物标记的解决方案显示,加密技术的能力可以支持在云环境中进行现实世界的基因组数据分析,从而取得了进步。

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