Ransomware has grown to be a dominant cybersecurity threat, by exfiltrating, encrypting or
destroying valuable user data, and causing numerous disruptions to victims. The severity of …

Rapid developments in network technologies and the amount and scope of data transferred
on networks are increasing day by day. Depending on this situation, the density and …

Feature selection (FS) is an important data pre-processing technique in classification. In
most cases, FS can improve classification accuracy and reduce feature dimension, so it can …

Due to the complexity and diversity of Industrial Internet of Things (IIoT) systems, which
include heterogeneous devices, legacy and new connectivity protocols and systems, and …

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 …

The detection of malware is a complex problem in the area of Internet security. Developing a
malware defense system that is less costly to detect large-scale malware is needed. This …

The increasing sophistication of malware threats has led to growing concerns in the anti-
malware community, as malware poses a significant danger to online users despite the …

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 …

Large-scale optimization problems (LSOPs) have become increasingly significant and
challenging in the evolutionary computation (EC) community. This article proposes a …

The most challenging issue in dealing with big datasets is the large number of their
dimensions. Feature selection is a technique for reducing the dimensionality of datasets by …