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 presents API-MalDetect, a new deep learning-based automated framework for
detecting malware attacks in Windows systems. The framework uses an NLP-based encoder …

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 …

Malware is a significant threat that has grown with the spread of technology. This makes
detecting malware a critical issue. Static and dynamic methods are widely used in the …

Malware pose a serious threat to the computers of individuals, enterprises and other
organizations. In the Windows operating system (OS), Application Programming Interface …

The struggle between security researchers and malware perpetuates an endless arms race.
Recent studies indicate that converting malware into grayscale images and using …

Harmful algal bloom (HAB) caused by Magalefidinium polykrikoides becomes frequent in
Korean coastal waters during the mid-1990s and is now annual events on the southern …

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 …

Nowadays, information security is a critical field of research since information technologies
develop rapidly. Consequently, the possible attacks are also evolving. One of the problems …

Conventional malware detection approaches have the overhead of feature extraction, the
requirement of domain experts, and are time-consuming and resource-intensive. Learning …