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Secure Algorithms for Biomedical Research in Public Clouds

dc.contributor.authorBeck, Martin
dc.contributor.authorHaupt, V. Joachim
dc.contributor.authorMoennich, Jan
dc.contributor.authorRoy, Janine
dc.contributor.authorJäkel, René
dc.contributor.authorSchroeder, Michael
dc.contributor.authorIsik, Zerrin
dc.date.accessioned2017-06-29T16:28:08Z
dc.date.available2017-06-29T16:28:08Z
dc.date.issued2014
dc.description.abstractAlgorithms from the biomedical domain have to face a rapid growth of biological data and therefore a rising demand for computing time. The predictive power of such algorithms is also further improving and becomes increasingly interesting for commercial applications. Cloud Computing – as an already established paradigm to elastically allocate computing resources on demand – offers flexible solutions to deal with the increasing request for compute power. However, security concerns remain when valuable research or business data are being processed in a Public Cloud. Herein, we describe – from the application and security perspective – three biomedical case studies from different domains: Patent annotation, cancer outcome prediction, and drug target prediction developed within the GeneCloud project. Our approach is to realize a data-centric security method to be able to compute on encrypted or blinded data in any non-trustworthy environment accessible by the user.en
dc.identifier.pissn0177-0454
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V., Fachgruppe PARS
dc.relation.ispartofPARS-Mitteilungen: Vol. 31, Nr. 1
dc.subjectCloud Computing
dc.subjectdata security
dc.subjectprivacy
dc.subjecttext-mining
dc.subjectoutcome prediction
dc.subjectdrug repositioning
dc.titleSecure Algorithms for Biomedical Research in Public Cloudsen
dc.typeText/Journal Article
gi.citation.publisherPlaceBerlin

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