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Detection and Prevention of Fraudulent in Using Credit Card

J. Maria Shyla Thomas

Abstract


Credit card transactions happen at every moment all over the world. People do their financial transactions using credit card either in online or offline. In the mean time frauds associated with it are also rising.  Fraud detection involves monitoring the behavior of users in order to estimate, detect or avoid unwanted behavior .In this paper, it is shown that credit card fraud that can be detected effectively using Hidden Markov Model (HMM). HMM could be trained with Hybrid Baum-Welch and Viterbi algorithms for better efficiency in detection.


Keywords


HMM, Fraudulent, Baum-Welch, Viterbi

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References


Yoram Singer, Manfred K. Warmuth.” Training Algorithms for Hidden Markov Models Using Entropy Based Distance Functions”

Nitika Kadam, Suryakant Soni, Devendra Puntambekar, Rahul KaulCredit “Card Fraud Detection Based on User Profile and Previous Transaction” Indian Journal of Research vol 2, Issue 3 March 2013

Avinash Ingole, Dr. R. C. Thool “Credit Card Fraud Detection Using Hidden Markov Model and Its Performance” International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 6, June 2013

Khyati Chaudhary. Bhawna “Credit Card Fraud: Bang in E-Commerce” International Journal of Computational Engineering Research / IJCER | May-June 2012 | Vol. 2 | Issue No.3 |935-941 ISSN: 2250–3005

Sam Mayes, Karl Tuyls, Bram Vanschoenwinkel, Bernard Manderick “Credit Card Fraud Detection Using Bayesian and Neural Networks”.

Hemlata Sahu, Shalini Shrma, Seema Gondhalakar , “ A Brief Overview on Data Mining Survey” IJCTEE Volume 1, Issue 3

Sonali N.Jadhav, ,Kiran Bhandari “Anomaly Detection Using Hidden Markov Model” International Journal of Computational Engineering Research Vol, 03 –Issue -, 7

V. Bhusari, S. Patil “Study of Hidden Markov Model in Credit Card Fraudulent Detection”, International Journal of Computer Applications (0975 – 8887) Volume 20– No.5, April 2011


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