Credit Card Fraud Detection Using Hidden Markov Model 论文

2008IEEE Transactions on Dependable and Secure Computing引用 527
Vehicle License Plate RecognitionImbalanced Data Classification TechniquesAdvanced Steganography and Watermarking Techniques

详细信息

发表期刊/会议
IEEE Transactions on Dependable and Secure Computing
发表日期
2008-01-01
发表年份
2008

关键词

Vehicle License Plate RecognitionImbalanced Data Classification TechniquesAdvanced Steganography and Watermarking Techniques

摘要

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.