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An investigation into financial fraud in online banking and card payment systems in the UK and ChinaSun, Yan January 2011 (has links)
This doctoral thesis represents an investigation into financial fraud in online banking and card payment systems in the UK and China, involving network security, online financial transactions, internet fraud, card payment systems and individuals' perception of and behaviours towards electronic environments. In contrast to previous studies, the research questions were tackled by survey questionnaires both in the UK and China, with a particular interest in fraud and attempted fraud. The main findings from the UK respondents were that those with higher IT skill and younger respondents are more likely to be defrauded on the internet. Certain types of online activities are associated with higher risks of fraud, these being internet banking; online shopping and media downloading. Furthermore, four predictors (internet banking, online education services, downloading media and length of debit card usage) provided significant effects in the logistic regression model to explain fraud occurrence in the UK. Based on the data collected in China, younger respondents were more likely to have higher general IT skill and higher educational qualifications. However, online shopping was the only online activity which was significantly correlated to fraud occurrence. Finally, two predictors (frequency of usage of online shopping and number of debit cards) were selected in the logistic regression model to explain fraud occurrence in China.
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Differential evolution technique on weighted voting stacking ensemble method for credit card fraud detectionDolo, Kgaugelo Moses 12 1900 (has links)
Differential Evolution is an optimization technique of stochastic search for a population-based vector, which is powerful and efficient over a continuous space for solving differentiable and non-linear optimization problems. Weighted voting stacking ensemble method is an important technique that combines various classifier models. However, selecting the appropriate weights of classifier models for the correct
classification of transactions is a problem. This research study is therefore aimed at exploring whether the Differential Evolution optimization method is a good approach for defining the weighting function. Manual and random selection of weights for voting credit card transactions has previously been carried out. However, a large number of fraudulent transactions were not detected by the classifier models. Which means that a technique to overcome the weaknesses of the classifier models is required. Thus, the problem of selecting the
appropriate weights was viewed as the problem of weights optimization in this study. The dataset was downloaded from the Kaggle competition data repository. Various machine learning algorithms were used to weight vote a class of transaction. The differential evolution optimization techniques was used as a weighting function. In
addition, the Synthetic Minority Oversampling Technique (SMOTE) and Safe Level Synthetic Minority Oversampling Technique (SL-SMOTE) oversampling algorithms were modified to preserve the definition of SMOTE while improving the performance. Result generated from this research study showed that the Differential Evolution
Optimization method is a good weighting function, which can be adopted as a systematic weight function for weight voting stacking ensemble method of various classification methods. / School of Computing / M. Sc. (Computing)
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Advance fee fraudTanfa, Denis Yomi 31 March 2006 (has links)
The focus of this thesis is on Advance Fee Fraud (419 scams) on how it is executed and more importantly, on how it can be prevented. The research addresses the origins of AFF, the nature and extent of this crime and how the perpetrators are able to defraud their victims. The research described, examined and analysed the crimes, the perpetrators, the victims, adjudication and the prevention strategies of this fraud. Information was gathered through literature and empirical research. A qualitative research method was used to gather information from AFF offenders who were incarcerated in South African prisons in 2005. The results of the empirical research were carefully examined, analyzed and integrated into the various chapters of this thesis. A theoretical framework was also developed in an attempt to explain this complex phenomenon. The findings and recommendations in terms of the crimes, the criminals, the victims, adjudication and prevention were also made and some suggestions for further research thereof were also cited. / Criminology / D. Litt. et Phil. (Criminology)
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Advance fee fraudTanfa, Denis Yomi 31 March 2006 (has links)
The focus of this thesis is on Advance Fee Fraud (419 scams) on how it is executed and more importantly, on how it can be prevented. The research addresses the origins of AFF, the nature and extent of this crime and how the perpetrators are able to defraud their victims. The research described, examined and analysed the crimes, the perpetrators, the victims, adjudication and the prevention strategies of this fraud. Information was gathered through literature and empirical research. A qualitative research method was used to gather information from AFF offenders who were incarcerated in South African prisons in 2005. The results of the empirical research were carefully examined, analyzed and integrated into the various chapters of this thesis. A theoretical framework was also developed in an attempt to explain this complex phenomenon. The findings and recommendations in terms of the crimes, the criminals, the victims, adjudication and prevention were also made and some suggestions for further research thereof were also cited. / Criminology and Security Science / D. Litt. et Phil. (Criminology)
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