Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/3568
Title: Service based credit card fraud detection using Oracle SOA suite
Authors: Ingole, Shubham
Abhishek, Kumar
Prusti, Debachudamani
Rath, Santanu Kumar
Keywords: SOA, Machine learningalgorithms
CNN,Oracle SOA suite,GCP
Issue Date: Dec-2020
Abstract: Credit card fraud detection techniques help to capture fraudulent transactions carried out by illegitimate users and thus prevent any misuse of the credit card. Due to the technological advancement,credit card usage has been on the rise of financial transactions keeping aside the risk of increase in number of fraudulent transactions. Thus, some sort of improved strategies are desired to be implemented in order to curb and avoid such fraudulent transactions.This study intends to propose a fraud detection technique by implementing various machine learning techniques on cloud platform which itself is based on service oriented architecture (SOA).SOA helps to create applications by making use of services available over the network. Further,this credit card fraud detection technique, focuses on orchestration of various services using Oracle SOA suite mingled with different machine learning models such as support vector machine(SVM), isolation forest, randomforest regressor, local outlier factor (LOF) and different neural networks such as multi layer perceptron(MLP), auto encoder and convolutional neural network (CNN).The output sofallthe machine learning models are integrated with Oracle SOA suite in order to provide proper agility and efficiency.And this Oracle SOA suite model has been deployed on Google cloud platform(GCP)for providing reliable solution in an online mode.A comparative analysis on performance of different machine learning algorithms has been presented for the ircritical assessment.Keywords: ,
Description: Copyright of this paper is with proceedings publisher
URI: http://hdl.handle.net/2080/3568
Appears in Collections:Conference Papers

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