Detecting SIM box fraud using neural network
One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine...
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2012
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my.utm.340512017-09-07T04:10:28Z http://eprints.utm.my/id/eprint/34051/ Detecting SIM box fraud using neural network Hussein Elmi, Abdikarim Ibrahim, Subariah Sallehuddin, Roselina One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine features found to be useful in identifying SIM box fraud subscriber are derived from the attributes of the Customer Database Record (CDR). Artificial Neural Networks (ANN) has shown promising solutions in classification problems due to their generalization capabilities. Therefore, supervised learning method was applied using Multi layer perceptron (MLP) as a classifier. Dataset obtained from real mobile communication company was used for the experiments. ANN had shown classification accuracy of 98.71 %. 2012 Conference or Workshop Item PeerReviewed Hussein Elmi, Abdikarim and Ibrahim, Subariah and Sallehuddin, Roselina (2012) Detecting SIM box fraud using neural network. In: The International Conference on IT Convergence and Security (ICITCS 2012). |
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One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine features found to be useful in identifying SIM box fraud subscriber are derived from the attributes of the Customer Database Record (CDR). Artificial Neural Networks (ANN) has shown promising solutions in classification problems due to their generalization capabilities. Therefore, supervised learning method was applied using Multi layer perceptron (MLP) as a classifier. Dataset obtained from real mobile communication company was used for the experiments. ANN had shown classification accuracy of 98.71 %. |
| format |
Conference or Workshop Item |
| author |
Hussein Elmi, Abdikarim Ibrahim, Subariah Sallehuddin, Roselina |
| spellingShingle |
Hussein Elmi, Abdikarim Ibrahim, Subariah Sallehuddin, Roselina Detecting SIM box fraud using neural network |
| author_facet |
Hussein Elmi, Abdikarim Ibrahim, Subariah Sallehuddin, Roselina |
| author_sort |
Hussein Elmi, Abdikarim |
| title |
Detecting SIM box fraud using neural network |
| title_short |
Detecting SIM box fraud using neural network |
| title_full |
Detecting SIM box fraud using neural network |
| title_fullStr |
Detecting SIM box fraud using neural network |
| title_full_unstemmed |
Detecting SIM box fraud using neural network |
| title_sort |
detecting sim box fraud using neural network |
| publishDate |
2012 |
| url |
http://eprints.utm.my/id/eprint/34051/ |
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1643649501422944256 |