Fan et al. [10]suggest the application of distributed data mining in credit card fraud detection. Brauseetal. [11]have developed an approach that involves advanced data mining … Credit CardFraud Detection Using Hidden Markov Model Abhinav Srivastava, Amlan Kundu, Shamik Sural, Senior Member, IEEE, and ArunK. Majumdar, Senior Member, IEEE Abstract—Due to a rapid advancement in the electronic commerce technology, the use of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for …

2RELATED WORK ON CREDIT CARD FRAUD DETECTION Credit card fraud detection has drawn a lot of research interest and a number of techniques, with special emphasis on data mining and neural networks, have been suggested. Ghoshand Reilly[4]have proposed credit card fraud detection withaneural network. They have built a detection system, which is trained on a large sample of labeled credit card account transactions. These transactions contain exam- plefraudcasesdue to lost cards, stolen cards, application fraud, counterfeit fraud, mail-order fraud, andnonreceived issue (NRI)fraud. Recently,Syedaetal.[5]have used pa rallel granular neural networks (PGNNs) for improving the speed of data mining and knowledge discovery process in credit card fraud detection. Acompletesystem has been imple- mentedforthis purpose. Stolfoetal. [6]suggestacredit card fraud detection system (FDS) usingmetalearning techniques to learn models of fraudulent credit card transactions. Metalearningisa general strategy that provides a means for combining and integratinga number of separately built classifiers or models.

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