Credit card fraud detection using artificial neural network

Abstract Frauds in credit card transactions are common today as most of us are using the credit card payment methods more frequently. This is due to the advancement of Technology and increase in online transaction resulting in frauds causing huge financial loss. Therefore, there is need for effective methods to reduce the loss. In addition, fraudsters find ways to steal the credit card information of the user by sending fake SMS and calls, also through masquerading attack, phishing attack and so on. This paper aims in using the multiple algorithms of Machine learning such as support vector machine (SVM), k-nearest neighbor (Knn) and artificial neural network (ANN) in predicting the occurrence of the fraud. Further, we conduct a differentiation of the accomplished supervised machine learning and deep learning techniques to differentiate between fraud and non-fraud transactions.

[1]  Changjun Jiang,et al.  Credit Card Fraud Detection via Kernel-Based Supervised Hashing , 2018, 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

[2]  Santanu Kumar Rath,et al.  Web service based credit card fraud detection by applying machine learning techniques , 2019, TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON).

[3]  Faouzia Benabbou,et al.  Fraud detection in credit card transaction using neural networks , 2019 .

[4]  G. Niveditha,et al.  Credit Card Fraud Detection using Random Forest Algorithm , 2019, International Journal for Research in Applied Science and Engineering Technology.

[5]  Sara Makki,et al.  An Experimental Study With Imbalanced Classification Approaches for Credit Card Fraud Detection , 2019, IEEE Access.

[6]  Changjun Jiang,et al.  Credit Card Fraud Detection: A Novel Approach Using Aggregation Strategy and Feedback Mechanism , 2018, IEEE Internet of Things Journal.

[7]  Mohamad Zamini,et al.  Credit Card Fraud Detection using autoencoder based clustering , 2018, 2018 9th International Symposium on Telecommunications (IST).

[8]  U. Srinivasulu Reddy,et al.  Credit Card Fraud Detection Using Non-Overlapped Risk Based Bagging Ensemble (NRBE) , 2017, 2017 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC).

[9]  S. Preeti,et al.  Analysis of Various Credit Card Fraud Detection Techniques , 2019, International Journal of Computer Sciences and Engineering.

[10]  Rameshwar Pratap,et al.  Ensemble learning for credit card fraud detection , 2018, COMAD/CODS.

[11]  Pawan Kumar,et al.  Credit Card Fraud Identification Using Machine Learning Approaches , 2019, 2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT).

[12]  Altyeb Altaher Taha,et al.  An Intelligent Approach to Credit Card Fraud Detection Using an Optimized Light Gradient Boosting Machine , 2020, IEEE Access.

[13]  Truong Thu Huong,et al.  Real Time Data-Driven Approaches for Credit Card Fraud Detection , 2018, ICEBA 2018.