Deep learning (DL) has proven to be effective in detecting sophisticated malware that is
constantly evolving. Even though deep learning has alleviated the feature engineering …

Machine learning-based malware analysis approaches are widely researched and
deployed in critical infrastructures for detecting and classifying evasive and growing …

Ransomware attacks have captured news headlines worldwide for the last few years due to
their criticality and intensity. Ransomware-as-a-service (RaaS) kits are aiding adversaries to …

In recent years, a significant amount of research has focused on analyzing the effectiveness
of machine learning (ML) models for malware detection. These approaches have ranged …

Cloud Computing (CC) has ushered in a paradigm shift in the provisioning of IT resources,
offering users enhanced cost-efficiency and streamlined infrastructure management …

Machine learning (ML) has seen exponential growth in recent years, finding applications in
various domains such as finance, medicine, and cybersecurity. Malware remains a …

Malware analysis and detection are still essential for maintaining the security of networks
and computer systems, even as the threat landscape shifts. Traditional approaches are …

The inclusion of Internet of Things (IoT) devices is growing rapidly in all application domains.
Smart Farming uses IoT devices to increase efficiency and optimize farming operations …

Cloud computing technology is known as a distributed computing network, which consists of
a large number of servers connected via the internet. This technology involves many …

Malware detection is of great significance for maintaining the security of information systems.
Malware obfuscation techniques and malware variants are increasingly emerging, but their …