Malware Classification Approaches Using Machine Learning Techniques: A Review

Malware has soared rapidly in the recent years and has become a danger to internet security. To counter the malware attacks, anti-malware programs have been designed. Anti-malware programs normally use the traditional signature-based detection technique. Researchers all over the world have worked towards the issue of malware detection and proposed diverse solutions. According to existing research, machine learning has demonstrated exceptional performance in the detection of malware. This paper presents a survey of malware detection methods using machine learning. We make an analysis of the present state of research from key components such as data used, feature extraction and classification. Finally, we gauge the future potential for exploration in malware detection area. This review could lay a foundation for future scholars to begin pioneering and innovative work in this discipline.