Use of fuzzy clustering and support vector machine for detecting fraud in mobile telecommunication networks Online publication date: Wed, 02-Mar-2016
by Sharmila Subudhi; Suvasini Panigrahi
International Journal of Security and Networks (IJSN), Vol. 11, No. 1/2, 2016
Abstract: This paper addresses the problem of finding out fraudulent calls in mobile phones by analysing the user's calling behaviour. In this work, we have used support vector machine (SVM) along with fuzzy clustering for detecting fraudulent usage of mobile phones. The reality mining data-set has been used for testing the efficacy of the proposed approach. A total of five relevant features are being used in creating the user profile from the user's call record. Fuzzy clustering is applied for generating the SVM classifier model. An anomaly is detected when a call pattern does not match with any of the normal patterns. Our experiments show promising results in terms of finding fraudulent calls without raising too many false alarms. Comparative studies are carried out on the proposed system by applying different types of SVMs along with various fuzzy clustering techniques for analysing the performance of the system.
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