A design methodology for web-based services to detect fraudulent transactions in credit card

Abstract

Financial fraud associated with the transactions of credit card leads to unauthorized access of performing credit card transactions indifferent platforms by intercepting important card credentials. In order to curb this problem, an effective fraud detection system is of primary importance for any financial institution. In the pro-posed methodology, a web-based fraud detection system has been designed considering two different protocols for the web-based services such as simple object access protocol (SOAP) and representational state transfer (REST). Further, for detecting the fraudulent transactions, these services are associated with five different ma-chine learning techniques such as support vector machine (SVM),multilayer perceptron (MLP), random forest regression, auto en-coder and isolation forest. The performance analysis of each ma-chine learning algorithm associated with SOAP and REST services are critically assessed. The web services have been designed based on concepts of service oriented architecture (SOA) by considering a middle ware family of software products i.e., Oracle SOA suite which is very often used by the software architects.