Detection of Mobile Phone Fraud Using Possibilistic Fuzzy C-Means Clustering and Hidden Markov Model

Sharmila Subudhi, Suvasini Panigrahi and Tanmay Kumar Behera
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Sharmila Subudhi: Veer Surendra Sai University of Technology, Sambalpur, India
Suvasini Panigrahi: Department of CSE and IT, Veer Surendra Sai University of Technology, Sambalpur, India
Tanmay Kumar Behera: Veer Surendra Sai University of Technology, Sambalpur, India

International Journal of Synthetic Emotions (IJSE), 2016, vol. 7, issue 2, 23-44

Abstract: This paper presents a novel approach for fraud detection in mobile phone networks by using a combination of Possibilistic Fuzzy C-Means clustering and Hidden Markov Model (HMM). The clustering technique is first applied on two calling features extracted from the past call records of a subscriber generating a behavioral profile for the user. The HMM parameters are computed from the profile, which are used to generate some profile sequences for training. The trained HMM model is then applied for detecting fraudulent activities on incoming call sequences. A calling instance is detected as forged when the new sequence is not accepted by the trained model with sufficiently high probability. The efficacy of the proposed system is demonstrated by extensive experiments carried out with Reality Mining dataset. Furthermore, the comparative analysis performed with other clustering methods and another approach recently proposed in the literature justifies the effectiveness of the proposed algorithm.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jse000:v:7:y:2016:i:2:p:23-44

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