Comparative analysis of binary and one-class classification techniques for credit card fraud data
The yearly increase in incidents of credit card fraud can be attributed to the rapid growth of e-
commerce. To address this issue, effective fraud detection methods are essential. Our …
commerce. To address this issue, effective fraud detection methods are essential. Our …
Detecting frauds and payment defaults on credit card data inherited with imbalanced class distribution and overlap** class problems: A systematic review
Credit card payments are one popular e-payment option apart from cash payments. Recent
reports show that credit card fraud and payment defaults are increasing annually and are …
reports show that credit card fraud and payment defaults are increasing annually and are …
Unsupervised anomaly detection of class imbalanced cognition data using an iterative cleaning method
The presence of class imbalance in machine learning datasets is a pervasive challenge that
often hampers the effectiveness of traditional machine learning models. In the context of …
often hampers the effectiveness of traditional machine learning models. In the context of …
One-class classification for credit card fraud detection: A detailed study with comparative insights from binary classification
Credit card fraud is a pervasive issue that causes significant financial loss, thus
underscoring the urgent need for effective detection techniques. In this book chapter on One …
underscoring the urgent need for effective detection techniques. In this book chapter on One …
Synthesizing class labels for highly imbalanced credit card fraud detection data
Acquiring labeled datasets often incurs substantial costs primarily due to the requirement of
expert human intervention to produce accurate and reliable class labels. In the modern data …
expert human intervention to produce accurate and reliable class labels. In the modern data …
Anomaly Detection in Key-Management Activities Using Metadata: A Case Study and Framework
Large scale enterprise networks often use Enterprise Key-Management (EKM) platforms for
unified management of cryptographic keys. Monitoring access and usage patterns of EKM …
unified management of cryptographic keys. Monitoring access and usage patterns of EKM …
Anomaly Detection in the Key-Management Interoperability Protocol Using Metadata
Large scale enterprise networks often use Enterprise Key-Management (EKM) platforms for
unified management of cryptographic keys. In such a system, requests and responses …
unified management of cryptographic keys. In such a system, requests and responses …
ITERADE-ITERative Anomaly Detection Ensemble for Credit Card Fraud Detection
Anti-money laundering (AML) efforts are critical not just for financial stability but also for
global security, as money laundering supports various criminal activities like terrorism …
global security, as money laundering supports various criminal activities like terrorism …
A Novel Approach to Synthesize Class Labels in Highly Imbalanced Large Data
A majority of the data being created today is unlabeled and the datasets that are labeled
often come at a high cost, primarily due to the need for human intervention. This is especially …
often come at a high cost, primarily due to the need for human intervention. This is especially …
Novel Techniques for Handling Imbalanced Data with Unsupervised Methods
RKL Kennedy - 2024 - search.proquest.com
In the modern data landscape, vast amounts of unlabeled data are continuously generated,
necessitating development of robust unsupervised techniques for handling unlabeled data …
necessitating development of robust unsupervised techniques for handling unlabeled data …