{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sig-db-leveraging-homomorphic-encryption-to","title":"SIG-DB: leveraging homomorphic encryption to Securely Interrogate privately held Genomic DataBases","arxiv_id":"1803.09565","date":"2018-03-26","proceeding":null,"authors":[],"abstract":"Genomic data are becoming increasingly valuable as we develop methods to\nutilize the information at scale and gain a greater understanding of how\ngenetic information relates to biological function. Advances in synthetic\nbiology and the decreased cost of sequencing are increasing the amount of\nprivately held genomic data. As the quantity and value of private genomic data\ngrows, so does the incentive to acquire and protect such data, which creates a\nneed to store and process these data securely. We present an algorithm for the\nSecure Interrogation of Genomic DataBases (SIG-DB). The SIG-DB algorithm\nenables databases of genomic sequences to be searched with an encrypted query\nsequence without revealing the query sequence to the Database Owner or any of\nthe database sequences to the Querier. SIG-DB is the first application of its\nkind to take advantage of locality-sensitive hashing and homomorphic encryption\nto allow generalized sequence-to-sequence comparisons of genomic data.","url_abs":"http://arxiv.org/abs/1803.09565v1","url_pdf":"http://arxiv.org/pdf/1803.09565v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sig-db-leveraging-homomorphic-encryption-to","repo_url":"https://github.com/BNext-IQT/GEMstone","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}