ER-index: a referential index for encrypted genomic databases

Ferdinando Montecuollo; Giovannni Schmid

doi:10.1016/j.is.2020.101668

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arXiv · 1910.02851

ER-index: a referential index for encrypted genomic databases

Ferdinando Montecuollo·Giovannni Schmid

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Abstract

Huge DBMSs storing genomic information are being created and engineerized for doing large-scale, comprehensive and in-depth analysis of human beings and their diseases. However, recent regulations like the GDPR require that sensitive data are stored and elaborated thanks to privacy-by-design methods and software. We designed and implemented ER-index, a new full-text index in minute space which was optimized for compressing and encrypting collections of genomic sequences, and for performing on them fast pattern-search queries. Our new index complements the E2FM-index, which was introduced to compress and encrypt collections of nucleotide sequences without relying on a reference sequence. When used on collections of highly similar sequences, the ER-index allows to obtain compression ratios which are an order of magnitude smaller than those achieved with the E2FM-index, but maintaining its very good search performance. Moreover, thanks to the ER-index multi-user and multiple-keys encryption model, a single index can store the sequences related to a population of individuals so that users may perform search operations only on the sequences to which they were granted access. The ER-index C++ source code plus scripts and data to assess the tool performance are available at: https://github.com/EncryptedIndexes/erindex.

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Ferdinando Montecuollo, Giovannni Schmid. 2019-10-07. ER-index: a referential index for encrypted genomic databases. https://doi.org/10.1016/j.is.2020.101668

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