Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …

The aim of this systematic literature review (SLR) is to provide a comprehensive overview of
the current state of Windows malware detection techniques, research issues, and future …

This paper provides a comprehensive review of the future of cybersecurity through
Generative AI and Large Language Models (LLMs). We explore LLM applications across …

Dynamic analysis enables detecting Windows malware by executing programs in a
controlled environment and logging their actions. Previous work has proposed training …

There has been a tremendous growth of edge devices connected to the network in recent
years. Although these devices make our life simpler and smarter, they need to perform …

Finding automated AI techniques to proactively defend against malware has become
increasingly critical. The ability of an AI model to correctly classify novel malware is …

Malware detection and classification are crucial for protecting digital devices and information
systems. Accurate identification of malware enables researchers and incident responders to …

Currently, the detection of malware to prevent cybersecurity breaches is a raising a concern
for millions of people around the globe. Even with the most recent updates, antivirus …

Malware is one of the most common and severe cyber threats today. Malware infects
millions of devices and can perform several malicious activities including compromising …

In the recent past, the level of cyber threats has changed drastically, leading to the current
transformation of the cybersecurity landscape. For example, emerging threats like Zero-day …