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[26 May 2014] A bachelor student at RTSLAB was awarded the best thesis award from IDA - Simon Andersson. more ...

[31 May 2012] A masters student at RTSLAB was awarded the best thesis award from IDA - Ulf Magnusson. more ...

[27 February 2008] A masters student at RTSLAB was awarded the best thesis award from IDA - Johan Sigholm. more ...

[03 March 2004] A masters student at RTSLAB was awarded the best thesis award from IDA - Tobias Chyssler. more ...

[01 Jul 2003] For second year in a row a masters student at RTSLAB was awarded the best thesis award from SNART - Mehdi Amirijoo. more ...

Master Thesis - Past Projects - Abstract

E-fraud, state of the art and counter measures

ID: LITH-IDA-EX--05/029--SE

This thesis investigates fraud and the situation on Internet with e-commerce today, to point on some potential threats and needed countermeasures. The work reviews several state of the art e-fraud schemes, techniques used in the schemes and statistics on the extent of e-fraud. This part shows that e-frauds are today both sophisticated and widespread. Since real world frauds are deemed impossible to fully cover in order to predict potential new e-frauds, the thesis adopts a different approach. It suggests two abstraction models for fraud cases, a protocol model and a functional model. These are used to perform analysis on case studies on both telecom frauds and e-frauds. The analysis presents characteristics for both types of frauds. Using one of the abstraction models, the functional model, conceptually similar cases among telecom frauds as well as e-fraud cases are identified. The similar cases in each category are then compared, using the other abstraction model, the protocol model. The study shows that concepts from telecom frauds already exist in e-frauds. Several challenges and some possibilities in e-fraud prevention and detection are also extracted in the comparative study of the different categories. The major consequence of the challenges is e-frauds

Keywords: E-fraud, e-commerce, telecom fraud, fraud detection, fraud classifications

Author(s): Bengt Bergman

Contact: Simin Nadjm-Tehrani

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