Secure Algorithms for Biomedical Research in Public Clouds
dc.contributor.author | Beck, Martin | |
dc.contributor.author | Haupt, V. Joachim | |
dc.contributor.author | Moennich, Jan | |
dc.contributor.author | Roy, Janine | |
dc.contributor.author | Jäkel, René | |
dc.contributor.author | Schroeder, Michael | |
dc.contributor.author | Isik, Zerrin | |
dc.date.accessioned | 2017-06-29T16:28:08Z | |
dc.date.available | 2017-06-29T16:28:08Z | |
dc.date.issued | 2014 | |
dc.description.abstract | Algorithms 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.pissn | 0177-0454 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V., Fachgruppe PARS | |
dc.relation.ispartof | PARS-Mitteilungen: Vol. 31, Nr. 1 | |
dc.subject | Cloud Computing | |
dc.subject | data security | |
dc.subject | privacy | |
dc.subject | text-mining | |
dc.subject | outcome prediction | |
dc.subject | drug repositioning | |
dc.title | Secure Algorithms for Biomedical Research in Public Clouds | en |
dc.type | Text/Journal Article | |
gi.citation.publisherPlace | Berlin |
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