Improved Credit Card Fraud Prediction using Edited Nearest Neighbors Learning Technique - Khan, Kajol; Dwivedi, Poornima (International Journal of Computer Sciences and Engineering, 2023)
Cloud computing and mobile computing have increasing its performance with rapid manner through numerous area of applications, these are extending such as digital payments, storage and confidential information accessing. Current technology offers several internet applications by using cloud based electronic payment methods, therefore security and confidentiality is necessary. According to national herald in India 42% frauds are identified in various fields from 1990 to 2020. Like “no fraud” agency in USA identified around 30% frauds since 1990, every year these frauds are increases with high ratios. Frauds did not have particular patterns, also change their behavior at every time. These frauds are most probably recognized at cloud based e-commerce and trade business websites. A real and precise fraud detection system must be developed in order to reduce this fraud ratio. In this exploration with the assistance of profound and AI improvement strategies has been utilized to recognize the cloud based fakes. So many, existed works settle this issue yet precision, F-score, review and precession are exceptionally less. Due to this impediment, in this work is introduced deep learning mechanisms like fully Edited Nearest Neighbor (ENN) and deep neural network (DNN). The DNN with ENN is best technique for credit card fraud prediction and achieve good accuracy.