Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets,
and services that are vital for the functioning and well-being of a society, economy, or nation …

Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …

Recent advances in online payment technologies combined with the impact of the COVID-
19 global pandemic has led to a significant escalation in the number of online transactions …

Credit risk analysis is a critical process in the financial industry, as it helps lenders assess
the likelihood of borrowers defaulting on their loans. With the advent of machine learning …

The use of powerful classifiers is broad and the problem of fraud detection tends to benefit
from similar solutions as well. The problem in the digital age cannot be disregarded as the …

Abstract Machine Learning (ML) has been categorized as a branch of Artificial Intelligence
(AI) under the Computer Science domain wherein programmable machines imitate human …

With the rapid developments in electronic commerce and digital payment technologies,
credit card transactions have increased significantly. Machine learning (ML) has been vital …

The class imbalance problem in finance fraud datasets often leads to biased prediction
towards the nonfraud class, resulting in poor performance in the fraud class. This study …

The recent increase in credit card fraud is rapidly has caused huge monetary losses for
individuals and financial institutions. Most credit card frauds are conducted online by …

Ensuring the safety of autonomous vehicles is becoming increasingly important with
ongoing technological advancements. In this paper, we suggest a machine learning-based …