Kamaruddin, Mohd Shafri (2006) Development of a Method for Fraud Severity Measurement Based On Usage Profiling. Masters thesis, Universiti Putra Malaysia.
The nature of fraud has changed from cloning fraud to subscription fraud, which makes specialized detection methodologies inadequate. Instead, the focus is on the detection methodologies that based on the subscriber’s calling activity or calling pattern, which can be roughly divided into two main categories: absolute analysis and differential analysis. Absolute analysis is capable at detecting the extremes of fraudulent activity. However, absolute analysis cannot trap all types of fraud especially usage behavior fraud related. An alternative approach to this problem is to perform a differential analysis against subscriber’s behavioral patterns. Certain behavioral patterns may be considered anomalous or abnormal for certain subscriber and potentially indicative of fraud but would be considered acceptable for another. In order to overcome the uncertainty in behavioral patterns, in this research, we propose to conduct the usage profiling at individual subscriber level. Usage profiling is a process of generating calling statistic based on predefined categories, which involve some form of aggregation from subscriber’s calling activity or CDR. Usage profiling process will generate two forms of usage profile : usage profile history (UPH) and current usage profile (CUP). In fraud detection system, comparison of these two types of usage profile will generate a measure known as fraud severity measurement. Implementation of the Hellinger distance for measuring a fraud severity, lack of detection accuracy as this method does not properly define the measurement scale as the Hellinger distance method will generate variation of values for fraud severity measurement. Therefore, it is very difficult to define the actual severity level of detected fraud. In this research, we propose a new method for measuring fraud severity. The advantages of the method are detection accuracy and detection speed. With the new method, the severity measurement scale is properly defined and the detection speed is faster than the Hellinger distance
|Item Type:||Thesis (Masters)|
|Chairman Supervisor:||Associate Professor Ramlan Mahmod, PhD|
|Call Number:||FSKTM 2006 14|
|Faculty or Institute:||Faculty of Computer Science and Information Technology|
|Deposited By:||Rosmieza Mat Jusoh|
|Deposited On:||07 Apr 2010 02:04|
|Last Modified:||27 May 2013 07:21|
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