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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 3 Issue 7, July 2014 | Rating: 6.2 / 10
Internet Banking Fraud Detection using HMM and BLAST-SSAHA Hybridization
Avanti H. Vaidya, S. W. Mohod
Abstract: With the rise and swift growth of E-Commerce, credit card uses for online purchases has increased dramatically and it caused sudden outbreak in the credit card fraud. Fraud is one of the major ethical issues in the credit card industry. With both online as well as regular purchase, credit card becomes the most popular mode of payment with cases of fraud associated with it are also increasing. For this purpose an efficient fraud detection system is necessary. This paper presents the detection of fraud transaction using BLAST-SSAHA Hybridization which is used for the optimization of dataset and Hidden Markov Model. At the same time we have tried to ensure that genuine transaction are not rejected by making use of one time password that was generated by bank server and sent to genuine cardholder.
Keywords: Internet Banking, Hidden Markov Model, BLAST-SSAHA Hybridization
Edition: Volume 3 Issue 7, July 2014,
Pages: 574 - 579