Privacy-preserving search for a similar genomic makeup in the cloud

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buir.contributor.authorAyday, Erman
buir.contributor.orcidAyday, Erman|0000-0003-3383-1081
dc.citation.epage2788en_US
dc.citation.issueNumber4en_US
dc.citation.spage2771en_US
dc.citation.volumeNumber19en_US
dc.contributor.authorZhu, X.
dc.contributor.authorVitenberg, R.
dc.contributor.authorVeeraragavan, N. R.
dc.contributor.authorAyday, Erman
dc.date.accessioned2023-02-15T07:57:50Z
dc.date.available2023-02-15T07:57:50Z
dc.date.issued2021-04-20
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractIncreasing affordability of genome sequencing and, as a consequence, widespread availability of genomic data opens up new opportunities for the field of medicine, as also evident from the emergence of popular cloud-based offerings in this area, such as Google Genomics [1]. To utilize this data more efficiently, it is crucial that different entities share their data with each other. However, such data sharing is risky mainly due to privacy concerns. In this article, we attempt to provide a privacy-preserving and efficient solution for the “similar patient search” problem among several parties (e.g., hospitals) by addressing the shortcomings of previous attempts. We consider a scenario in which each hospital has its own genomic dataset and the goal of a physician (or researcher) is to search for a patient similar to a given one (based on a genomic makeup) among all the hospitals in the system. To enable this search, we propose a hierarchical index structure to index each hospital’s dataset with low memory requirement. Furthermore, we develop a novel privacy-preserving index merging mechanism that generates a common search index from individual indices of each hospital to significantly improve the search efficiency. We also consider the storage of medical information associated with genomic data of a patient (e.g., diagnosis and treatment). We allow access to this information via a fine-grained access control policy that we develop through the combination of standard symmetric encryption and ciphertext policy attribute-based encryption. Using this mechanism, a physician can search for similar patients and obtain medical information about the matching records if the access policy holds. We conduct experiments on large-scale genomic data and show the high efficiency of the proposed scheme.en_US
dc.description.provenanceSubmitted by Fatma Kaya (fattttoky.55@gmail.com) on 2023-02-15T07:57:50Z No. of bitstreams: 1 Privacy-preserving_search_for_a_similar_genomic_makeup_in_the_cloud.pdf: 2472697 bytes, checksum: 6e6455ec12097cf6a2bf249fca73538e (MD5)en
dc.description.provenanceMade available in DSpace on 2023-02-15T07:57:50Z (GMT). No. of bitstreams: 1 Privacy-preserving_search_for_a_similar_genomic_makeup_in_the_cloud.pdf: 2472697 bytes, checksum: 6e6455ec12097cf6a2bf249fca73538e (MD5) Previous issue date: 2021-04-20en
dc.identifier.doi10.1109/TDSC.2021.3074327en_US
dc.identifier.eissn1941-0018
dc.identifier.issn15455971
dc.identifier.urihttp://hdl.handle.net/11693/111300
dc.language.isoEnglishen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.isversionofhttps://www.doi.org/10.1109/TDSC.2021.3074327en_US
dc.source.titleIEEE Transactions on Dependable and Secure Computingen_US
dc.subjectGenome privacyen_US
dc.subjectDataset outsourcingen_US
dc.subjectSimilar patient searchen_US
dc.titlePrivacy-preserving search for a similar genomic makeup in the clouden_US
dc.typeArticleen_US

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