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|Betreuer=Tobias Dehling, Ali Sunyaev
 
|Betreuer=Tobias Dehling, Ali Sunyaev
 
|Forschungsgruppe=Critical Information Infrastructures
 
|Forschungsgruppe=Critical Information Infrastructures
|Abschlussarbeitsstatus=In Bearbeitung
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|Abschlussarbeitsstatus=Abgeschlossen
 
|Beginn=2019/12/13
 
|Beginn=2019/12/13
 
|Abgabe=2020/07/02
 
|Abgabe=2020/07/02

Aktuelle Version vom 19. August 2020, 13:39 Uhr



Design Recommendations in Information Systems: Information Privacy Mechanisms that Account for Privacy Needs


Viet Duc Le



Informationen zur Arbeit

Abschlussarbeitstyp: Master
Betreuer: Tobias Dehling, Ali Sunyaev
Forschungsgruppe: Critical Information Infrastructures

Archivierungsnummer: 4239
Abschlussarbeitsstatus: Abgeschlossen
Beginn: 13. Dezember 2019
Abgabe: 02. Juli 2020

Weitere Informationen

Abstract: Nowadays information system environments are characterized by increasing information inter-connectedness and complexity. It is often difficult for users to determine how much of their data may be collected and how it might be used. For them, it is also nearly impossible to fully assess what privacy vulnerabilities they might expose themselves to, if they decide to interact with a given information system. Accordingly, more and more information privacy tools are available to meet user preferences. But the tools still have room for improvements. For example, often users ignore notices about information privacy policies as they are too long and complex to read. Since users do not read them, their expectations regarding data practices do not match actual data practices. The conse-quential mismatches between information privacy practices and up-to-date users’ expectations may result in users exposing themselves to unanticipated information privacy risks. Consequently, this work aims to capture the up-to-date users' expectations and experiences re-garding the information privacy tools through constructive interviews. Based on this, starting points - in the form of improvement approaches and deficits - will be identified for generating user problem–oriented and information privacy–enhancing design recommendations. Finally, by doing this the users should be able to make effective information privacy decisions.