Malware detection has become a major concern due to the increasing number and
complexity of malware. Traditional detection methods based on signatures and heuristics …

This comprehensive review provides an in-depth analysis of graph theory, various graph
types, and the role of graph visualization in scientific studies. Graphs serve as powerful tools …

Analyzing malware based on API call sequence is an effective approach as the sequence
reflects the dynamic execution behavior of malware. Recent advancements in deep learning …

Dynamic malware analysis that monitors the sequences of API calls of the program in a
sandbox has been proven to be effective against code obfuscation and unknown malware …

With the rapid increase in the number of malware, the detection and classification of
malware have become more challenging. In recent years, many malware classification …

In recent studies, convolutional neural networks (CNNs) are mostly used as dynamic
techniques for visualization-based malware classification and detection. Though vision …

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 …

Abstract Application Program Interface (API) calls are widely used in dynamic Windows
malware analysis to characterize the run-time behavior of malware. Researchers have …

Most malware detectors rely on machine-learning approaches. However, new malware
samples are growing very fast day by day, and their labeling is very expensive …

With the continuous development and popularization of the Internet, there has been an
increasing number of network security problems appearing. Among them, the rapid growth …