Fast confidential search for bio-medical data using Bloom filters and Homomorphic Cryptography

H. Perl, Yassene Mohammed, Michael Brenner, Matthew Smith
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引用次数: 20

Abstract

Data protection is a challenge when outsourcing medical analysis, especially if one is dealing with patient related data. While securing transfer channels is possible using encryption mechanisms, protecting the data during analyses is difficult as it usually involves processing steps on the plain data. A common use case in bioinformatics is when a scientist searches for a biological sequence of amino acids or DNA nucleotides in a library or database of sequences to identify similarities. Most such search algorithms are optimized for speed with less or no consideration for data protection. Fast algorithms are especially necessary because of the immense search space represented for instance by the genome or proteome of complex organisms. We propose a new secure exact term search algorithm based on Bloom filters. Our algorithm retains data privacy by using Obfuscated Bloom filters while maintaining the performance needed for real-life applications. The results can then be further aggregated using Homomorphic Cryptography to allow exact-match searching. The proposed system facilitates outsourcing exact term search of sensitive data to on-demand resources in a way which conforms to best practice of data protection.
快速机密搜索生物医学数据使用布隆过滤器和同态密码学
在外包医疗分析时,数据保护是一个挑战,特别是在处理与患者相关的数据时。虽然可以使用加密机制保护传输通道,但在分析期间保护数据是困难的,因为它通常涉及对普通数据的处理步骤。生物信息学中的一个常见用例是当科学家在序列库或数据库中搜索氨基酸或DNA核苷酸的生物序列以识别相似性时。大多数这样的搜索算法都是为了提高速度而优化的,很少或根本没有考虑数据保护。由于复杂生物体的基因组或蛋白质组所代表的巨大搜索空间,快速算法尤其必要。提出了一种基于Bloom过滤器的安全精确词搜索算法。我们的算法通过使用模糊的Bloom过滤器来保留数据隐私,同时保持实际应用所需的性能。然后可以使用同态加密进一步聚合结果,以允许精确匹配搜索。建议的系统以符合资料保护最佳实务的方式,方便将敏感资料的准确词项搜寻外判给按需资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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