Credit Card Fraud Research Paper

CREDIT CARD FRAUD DETECTION USING HIDDEN MARKOV MODEL WITH IMPROVED K-MEANS CLUSTERING ALGORITHM

Keerthi A , Remya MS

ABSTRACT

With the advancement in electronic commerce and internet commerce, credit card becomes the most popular mode of payment. Credit cards are convenient substitute for cash or cheque. The increasing use of credit cards for everyday business and online activities has increased the risk of fraud as criminals take advantage of technology to produce counterfeit cards, obtain account details and conduct fraudulent transactions. Hidden Markov Model is a simple and perfect solution for addressing detection of fraud transaction through credit card. In this paper, it is shown that credit card fraud can be detected more efficiently

Here the different steps in credit card transaction processing are represented as the underlying stochastic process of an HMM, the ranges of transaction amount are used as the observation symbols, and the types of item have been considered to be states of the HMM. The system is also scalable for handling large volumes of transactions. Shailesh S. Dhok[3] has suggested a method for finding the spending profile of card holders, as well as application of this knowledge in deciding the value of observation symbols and initial estimate of the model parameters using 2 modules-Online shopping and Fraud detection system.It has also been explained how the HMM can detect whether an incoming transaction is fraudulent or not. V. Bhusari1, S. Patil [4] have proposed a fraud detection system which is scalable for handling vast volumes of transactions data processing and it gives genuine and vast result than existing system.The HMM makes the processing of detection very easy and tries to remove the complexity.It shows that 88% transactions are genuine and very low faulse alarm which is about 8% of total number of transactions. Ashphak P. Khan, Vinod S. Mahajan, Shehzad H. Shaikh , Akash B. Koli [5] have proposed a system in which the transaction amounts are divided into 3 categories ie,

Majumdar, Senior Member, IEEE -2008

[2] “Anomaly Detection Using Hidden Markov Model”-1,Sonali N.Jadhav, 2,Kiran Bhandari 1M.E Scholar, 1,2,Assitant Professor, Thakur College Of Engineering And Technology, Mumbai, India-2013

[3] “Credit Card Fraud Detection Using Hidden Markov Model”-Shailesh S. Dhok- March 2012

[4] “Application of Hidden Markov Model in Credit Card Fraud Detection”-V. Bhusari1, S. Patil1 1Department of Computer Technology, College of Engineering,

Bharati Vidyapeeth, Pune, India, 400011- November 2011

[5] “Credit Card Fraud Detection System through Observation Probability Using Hidden Markov Model”-Ashphak P. Khan1, Vinod S. Mahajan2,Shehzad H. Shaikh3, Akash B. Koli4 North Maharashtra University- Jalgaon,D.N.Patel College of Engineering, Shahada, India- October-December 2013

[6] “Credit Card Fraud Detection by Improving K-Means”-Mahesh Singh, Aashima, Sangeeta Raheja- May 2014

[7] Credit Card Fraud Recognition by Modifying K-Means-Mahesh Sin, Ashima, Sangeeta Raheja, CSE DepartmentMaharshi Dayanand University,Rohtak-May