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Improving e-commerce fraud investigations in virtual, inter-institutional teams: Towards an approach based on Semantic Web technologies

  • There is a dramatic shift in credit card fraud from the offline to the online world. Large online retailers have tried to establish countermeasures and transaction data analysis technologies to lower the rate of fraudulent transactions to a manageable amount. But as retailers will always have to make a trade-off between the performance of the transaction processing, the usability of the web shop, and the overall security of it, one can assume that e-commerce fraud will still happen in the future. Thus, retailers have to collaborate with relevant business partners on the incident to find a common ground and take coordinated (legal) actions against it. Trying to combine the information from different stakeholders will face issues due to different wordings and data formats, competing incentives of the stakeholders to participate on information sharing, as well as possible sharing restrictions that prevent them from making the information available to a larger audience. Moreover, as some of the information might be confidential or business-critical to at least one of the parties involved, a centralized system (e.g. a service in the public cloud) can not be used. This Master Thesis is therefore analysing how far a computer supported collaborative work system based on peer-to-peer communication and Semantic Web technologies can improve the efficiency and effectivity of e-commerce fraud investigations within an inter-institutional team.

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Verfasserangaben:Andreas Gerlach
Gutachter:Kristian Fischer, Stephan Pavlovic
Veröffentlichende Institution:Hochschulbibliothek der Technischen Hochschule Köln
Titel verleihende Institution:Technische Hochschule Köln
Datum des Hochladens:30.09.2016
Freies Schlagwort / Tag:E-commerce fraud investigation; Semantic Web; Shared Information Spaces
Fakultäten und Zentrale Einrichtungen:Informatik und Ingenieurwissenschaften (F10) / Fakultät 10 / Advanced Media Institute
CCS-Klassifikation:J. Computer Applications
DDC-Sachgruppen:600 Technik, Medizin, angewandte Wissenschaften
Open Access:Open Access
Lizenz (Deutsch):License LogoCreative Commons - Namensnennung-Weitergabe unter gleichen Bedingungen