Abstract
Genomic data are becoming increasingly valuable as we develop methods to utilize the information at scale and gain a greater understanding of how genetic information relates to biological function. Advances in synthetic biology and the decreased cost of sequencing are increasing the amount of privately held genomic data. As the quantity and value of private genomic data grows, so does the incentive to acquire and protect such data, which creates a need to store and process these data securely. We present an algorithm for the Secure Interrogation of Genomic DataBases (SIG-DB). The SIG-DB algorithm enables databases of genomic sequences to be searched with an encrypted query sequence without revealing the query sequence to the Database Owner or any of the database sequences to the Querier. SIG-DB is the first application of its kind to take advantage of locality-sensitive hashing and homomorphic encryption to allow generalized sequence-to-sequence comparisons of genomic data.
Highlights
Genomic information is becoming valuable to a variety of applications, including healthcare and industry
Genomic data are becoming increasingly valuable as we develop methods to utilize the information at scale and gain a greater understanding of how genetic information relates to biological function
We present an algorithm for the Secure Interrogation of Genomic DataBases (SIG-DB)
Summary
Genomic information is becoming valuable to a variety of applications, including healthcare and industry. Biological data privacy and security is becoming increasingly important, especially as our understanding of how genetic information relates to biological function continues to grow. Researchers who want to study the genetics of disease may wish to compare patient genome databases in a way that allows data mining while complying with HIPAA obligations. Synthetic biology is transforming industrial practices, where microorganisms are exploited to produce commercial products, resulting in customized microbes and unique genomic data. The growing amount of privately held and proprietary genomic information, and the lack of secure computation techniques for sequence-to-sequence comparisons on that data, could hinder the timely genomic analysis of the novel microorganism
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