Credit card fraud detection using a new hybrid machine learning architecture
The negative effect of financial crimes on financial institutions has grown dramatically over
the years. To detect crimes such as credit card fraud, several single and hybrid machine …
the years. To detect crimes such as credit card fraud, several single and hybrid machine …
A review of machine learning applications for credit card fraud detection with a case study
Z Faraji - SEISENSE Journal of Management, 2022 - journal.seisense.com
Purpose-This paper aims to highlight the widely used supervised techniques applied for
fraud detection. In addition, this paper aims to apply some techniques to evaluate their …
fraud detection. In addition, this paper aims to apply some techniques to evaluate their …
E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review
The e-commerce industry's rapid growth, accelerated by the COVID-19 pandemic, has led to
an alarming increase in digital fraud and associated losses. To establish a healthy e …
an alarming increase in digital fraud and associated losses. To establish a healthy e …
Variable-length multivariate time series classification using ROCKET: A case study of incident detection
Multivariate time series classification is a machine learning problem that can be applied to
automate a wide range of real-world data analysis tasks. RandOm Convolutional KErnel …
automate a wide range of real-world data analysis tasks. RandOm Convolutional KErnel …
Bibliometric Analysis of Intelligent Systems for Early Anomaly Detection in Oil and Gas Contracts: Exploring Recent Progress and Challenges
LF Cardona, JA Guzmán-Luna, JA Restrepo-Carmona - Sustainability, 2024 - mdpi.com
The oil and gas industries are crucial to global economies, influencing geopolitics, driving
technological advancements, employing millions, and impacting financial markets. The …
technological advancements, employing millions, and impacting financial markets. The …
An analysis on fraud detection in credit card transactions using machine learning techniques
Today, digitization is turning popular because of the ease and convenience of utilizing e-
commerce. People are selecting on-line payments and electronic shopping due to the …
commerce. People are selecting on-line payments and electronic shopping due to the …
Generative adversarial neural networks based oversampling technique for imbalanced credit card dataset
S El Kafhali, M Tayebi - 2022 6th SLAAI International …, 2022 - ieeexplore.ieee.org
The imbalanced dataset is a challenging issue in many classification tasks. Because it leads
a machine learning algorithm to poor generalization and performance. The imbalanced …
a machine learning algorithm to poor generalization and performance. The imbalanced …
A convolutional neural network model for credit card fraud detection
Nowadays, online transactions through various ecommerce platforms are becoming more
prevalent, and Credit Card (CC) is significantly used in various online transactions …
prevalent, and Credit Card (CC) is significantly used in various online transactions …
Forensic Credit Card Fraud Detection Using Deep Neural Network
B Fakiha - Journal of Southwest Jiaotong University, 2023 - jsju.org
This paper describes the ways in which forensic credit card fraud detection can be achieved
using deep neural network (DNN). The problem that this research addresses is to identify a …
using deep neural network (DNN). The problem that this research addresses is to identify a …
An intelligent credit card fraudulent activity detection using hybrid deep learning algorithm
N Krishnavardhan, M Govindarajan… - Multimedia Tools and …, 2024 - Springer
Abstract Problem Statement With the rapid growth of internet usage, businesses, including
those in the financial sector, are increasingly providing their services online. Consequently …
those in the financial sector, are increasingly providing their services online. Consequently …