CREDIT CARD FRAUD DETECTION SYSTEM USING SUPPORT VECTOR MACHINE

ABSTRACT

Combating credit card fraud come with traditional prevention techniques such as PINs, passwords and identification systems however these have become inadequate in modern banking systems (Delwar et al, 2010). With a more electronic smart card like credit card, the rate of credit card fraud is also increasing. The huge transactional services are often eyed by cyber criminals to conduct fraudulent activities using the credit card services. The aim of this research is to develop a Credit Card Fraud Detection System using support vector machine. The application is designed using mainly the Java technology, it is designed as a web application so it can run on browsers, as a result, the user interfaces are developed using web technologies such as HTML5, CSS3 and JavaScript. The application logic is developed using Java beans and Java Servlet. The application is designed using the Model-View-Controller approach (MVC). The data persistent layer is maintained using the My SQL relational database. The dataset totaling 2000 entries was gotten from kaggle dataset repository. The dataset was split into test set (1000 entries) and train set (1000). The train set was used to train the support vector machine algorithm to produce a classification model. The test set was used to test the model trained to obtain the accuracy, F1 and confusion matrix values. The precision obtained for the single class SVM method, was of about 80%, which represents a significant improvement in comparison to similar works reference.