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 …

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 …

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 …

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

Insurance companies have focused on medicare fraud detection to reduce financial losses
and reputational harm because medicare fraud causes tens of billions of dollars in damage …

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 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 …

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 …

Flooding is a global threat and predicting flood risk accurately is vital for effective mitigation
and increasing society's awareness of the negative impacts of floods. Over the years …