Securing Online Banking Transaction using Predictive Approach of Hidden Markov Model
Author(s) -
D. Sangita,
S. Madhuri
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015906603
Subject(s) - computer science , database transaction , hidden markov model , markov chain , artificial intelligence , data mining , machine learning , database
Due to a Fast growth in the electronic commerce technology, popularity of online banking and online shopping is growing day by day. While e-commerce is still gaining popularity, it also provides ground for fraudsters who try to misuse the transparency of online purchases and the transfer of credit card records. In this paper, proposed model the sequence of operation in online banking transaction processing using a Hidden Markov Model (HMM) and describe how it can be used for the detection of frauds. An HMM is initially trained with the normal behaviour of a cardholder. If current transaction is not accepted by the trained model with good probability, it is treated as fraudulent. And one time password is send to mobile of card holder.
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