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Credit Card Fraud Detection Using Hidden Markov Model
January-March 2008 (vol. 5 no. 1)
pp. 37-48
The Internet has taken its place beside the telephone and the television as an important part of people's lives. Consumers rely on the Internet to shop, bank and invest online. Most online shoppers use credit cards to pay for their purchases. As credit card becomes the most popular mode of payment, cases of fraud associated with it are also increasing. In this paper, we model the sequence of operations in credit card transaction processing using a Hidden Markov Model (HMM) and show how it can be used for the detection of frauds. An HMM is trained with normal behavior of cardholder. If an incoming credit card transaction is not accepted by the HMM with sufficiently high probability, it is considered to be fraudulent. We present detailed experimental results to show the effectiveness of our approach.

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Index Terms:
Electronic Commerce, Security and Protection
Abhinav Srivastava, Amlan Kundu, Shamik Sural, Arun Majumdar, "Credit Card Fraud Detection Using Hidden Markov Model," IEEE Transactions on Dependable and Secure Computing, vol. 5, no. 1, pp. 37-48, Jan.-March 2008, doi:10.1109/TDSC.2007.70228
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