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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorBelhajjame, Khalid
dc.contributor.authorFaci, Noura
HAL ID: 5279
dc.contributor.authorMaamar, Zakaria
dc.contributor.authorBurégio, Vanilson
dc.contributor.authorSoares, Edvan
dc.contributor.authorBarhamgi, Mahmoud
dc.date.accessioned2021-11-02T14:43:40Z
dc.date.available2021-11-02T14:43:40Z
dc.date.issued2020
dc.identifier.issn1436-5057
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22152
dc.language.isoenen
dc.subjectPrivacyen
dc.subjecte-Scienceen
dc.subjectWorkflowen
dc.subject.ddc005en
dc.titleOn privacy-aware eScience workflowsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenComputing-intensive experiments in modern sciences have become increasingly data-driven illustrating perfectly the Big-Data era. These experiments are usually specified and enacted in the form of workflows that would need to manage (i.e., read, write, store, and retrieve) highly-sensitive data like persons’ medical records. We assume for this work that the operations that constitute a workflow are 1-to-1 operations, in the sense that for each input data record they produce a single data record. While there is an active research body on how to protect sensitive data by, for instance, anonymizing datasets, there is a limited number of approaches that would assist scientists with identifying the datasets, generated by the workflows, that need to be anonymized along with setting the anonymization degree that must be met. We present in this paper a solution privacy requirements of datasets used and generated by a workflow execution. We also present a technique for anonymizing workflow data given an anonymity degree.en
dc.relation.isversionofjnlnameComputing
dc.relation.isversionofjnlvol102en
dc.relation.isversionofjnlissue5en
dc.relation.isversionofjnldate2020-05
dc.relation.isversionofjnlpages1171–1185en
dc.relation.isversionofdoi10.1007/s00607-019-00783-8en
dc.relation.isversionofjnlpublisherSpringeren
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2021-11-02T14:40:48Z
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