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Avoiding Unintended Flows of Personally Identifiable Information - Enterprise Identity Management and Online Social Networks

Labitzke, Sebastian

Abstract:

This dissertation 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.


Volltext §
DOI: 10.5445/IR/1000036761
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Telematik (TM)
Scientific Computing Center (SCC)
Publikationstyp Hochschulschrift
Publikationsjahr 2013
Sprache Englisch
Identifikator urn:nbn:de:swb:90-367613
KITopen-ID: 1000036761
Verlag Karlsruher Institut für Technologie (KIT)
Art der Arbeit Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Telematik (TM)
Prüfungsdaten 19.07.2013
Schlagwörter Enterprise Identity and Access Management, SAML, Online Social Networks, Big Data Analytics
Relationen in KITopen
Referent/Betreuer Hartenstein, H.
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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