A systematic review of literature on credit card cyber fraud detection using machine and deep learning

EALM Btoush, X Zhou, R Gururajan, KC Chan… - PeerJ Computer …, 2023 - peerj.com
The increasing spread of cyberattacks and crimes makes cyber security a top priority in the
banking industry. Credit card cyber fraud is a major security risk worldwide. Conventional …

Survey of credit card anomaly and fraud detection using sampling techniques

M Alamri, M Ykhlef - Electronics, 2022 - mdpi.com
The rapid growth in e-commerce has resulted in an increasing number of people shopping
online. These shoppers depend on credit cards as a payment method or use mobile wallets …

Utilizing convolutional neural networks to classify monkeypox skin lesions

EHI Eliwa, AM El Koshiry, T Abd El-Hafeez… - Scientific reports, 2023 - nature.com
Monkeypox is a rare viral disease that can cause severe illness in humans, presenting with
skin lesions and rashes. However, accurately diagnosing monkeypox based on visual …

Enhancing credit card fraud detection through a novel ensemble feature selection technique

H Wang, Q Liang, JT Hancock… - 2023 IEEE 24th …, 2023 - ieeexplore.ieee.org
Identifying fraudulent activities in credit card transactions is an inherent component of
financial computing. The focus of our research is on the Credit Card Fraud Detection …

A Hybrid Convolutional Neural Network and Support Vector Machine‐Based Credit Card Fraud Detection Model

T Berhane, T Melese, A Walelign… - Mathematical …, 2023 - Wiley Online Library
Credit card fraud is a common occurrence in today's society because the majority of us use
credit cards as a form of payment more frequently. This is the outcome of developments in …

Improving medicare fraud detection through big data size reduction techniques

H Wang, JT Hancock… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Classification models serve as effective tools for Medicare fraud detection, but their
performance can be influenced by a number of factors. This paper focuses on addressing …

Stone decision engine accurately predicts stone removal and treatment complications for shock wave lithotripsy and laser ureterorenoscopy patients

PA Noble, BD Hamilton, G Gerber - Plos one, 2024 - journals.plos.org
Kidney stones form when mineral salts crystallize in the urinary tract. While most stones exit
the body in the urine stream, some can block the ureteropelvic junction or ureters, leading to …

Feature selection strategies: a comparative analysis of SHAP-value and importance-based methods

H Wang, Q Liang, JT Hancock, TM Khoshgoftaar - Journal of Big Data, 2024 - Springer
In the context of high-dimensional credit card fraud data, researchers and practitioners
commonly utilize feature selection techniques to enhance the performance of fraud detection …

Modified focal loss in imbalanced XGBoost for credit card fraud detection

D Trisanto, N Rismawati… - … Journal of Intelligent …, 2021 - repository.stmi.ac.id
The development of credit card use in Indonesia has not been matched by the security
provided by credit card service providers. This resulted in significant losses both in terms of …

XGBoost based solutions for detecting fraudulent credit card transactions

S El Kafhali, M Tayebi - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Due to the emigration of businesses to the internet, credit cards have become a widely used
tool for customers to pay for purchases both online and offline. However, fraudsters try to …