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A security framework for population-scale genomics analysis
KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0002-9484-6714
KTH, School of Computer Science and Communication (CSC), Centres, Centre for High Performance Computing, PDC. KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).ORCID iD: 0000-0002-9901-9857
2015 (English)In: Proceedings of the 2015 International Conference on High Performance Computing and Simulation, HPCS 2015, IEEE conference proceedings, 2015, 106-114 p.Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

Biobanks store genomic material from identifiable individuals. Recently many population-based studies have started sequencing genomic data from biobank samples and cross-linking the genomic data with clinical data, with the goal of discovering new insights into disease and clinical treatments. However, the use of genomic data for research has far-reaching implications for privacy and the relations between individuals and society. In some jurisdictions, primarily in Europe, new laws are being or have been introduced to legislate for the protection of sensitive data relating to individuals, and biobank-specific laws have even been designed to legislate for the handling of genomic data and the clear definition of roles and responsibilities for the owners and processors of genomic data. This paper considers the security questions raised by these developments. We introduce a new threat model that enables the design of cloud-based systems for handling genomic data according to privacy legislation. We also describe the design and implementation of a security framework using our threat model for BiobankCloud, a platform that supports the secure storage and processing of genomic data in cloud computing environments.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 106-114 p.
Keyword [en]
Access Control, Cloud Computing, Genomics, Privacy, Security, Data privacy, Digital storage, Genes, Population statistics, Clinical treatments, Cloud computing environments, Design and implementations, Genomics analysis, Privacy legislation, Security frameworks, Data handling
National Category
Bioinformatics and Systems Biology Other Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-181631DOI: 10.1109/HPCSim.2015.7237028ISI: 000375684100014Scopus ID: 2-s2.0-84948424681ISBN: 9781467378123 (print)OAI: oai:DiVA.org:kth-181631DiVA: diva2:907568
Conference
13th International Conference on High Performance Computing and Simulation, HPCS 2015, 20 July 2015 through 24 July 2015
Note

QC 20160229

Available from: 2016-02-29 Created: 2016-02-02 Last updated: 2016-06-20Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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