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dc.contributor.authorLabitzke, Sebastian*
dc.date.accessioned2021-02-11T08:48:07Z
dc.date.available2021-02-11T08:48:07Z
dc.date.issued2013*
dc.date.submitted2019-07-30 20:02:01*
dc.identifier35375*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/41743
dc.description.abstractThis work addresses potentially occurring unintended flows of personally identifiable information (PII) within two fields of research, i.e., enterprise identity management and online social networks. For that, we investigate which pieces of PII can how often be gathered, correlated, or even be inferred by third parties that are not intended to get access to the specific pieces of PII. Furthermore, we introduce technical measures and concepts to avoid unintended flows of PII.*
dc.languageEnglish*
dc.subjectQA75.5-76.95*
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer scienceen_US
dc.subject.otherBig Data Analytics*
dc.subject.otherEnterprise Identity and Access Management*
dc.subject.otherOnline Social Networks*
dc.subject.otherSAML*
dc.subject.otherFacebook*
dc.titleAvoiding Unintended Flows of Personally Identifiable Information : Enterprise Identity Management and Online Social Networks*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000036269*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783731500940*
oapen.pagesXVIII, 196 p.*
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeInternal editor
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityScientific or Editorial Board
peerreview.id8ad5c235-9810-49eb-b358-27c8675324d9
peerreview.titleDissertations (Dissertationen)


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