Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges and Future Directions

Malware has emerged as a cyber security threat that continuously changes to target computer systems, smart devices, and extensive networks with the development of information technologies. As result, malware detection always been major worry difficult issue, owing shortcomings in performance accuracy, analysis type, approaches fail identify unexpected attacks. This paper seeks conduct thorough literature review offer taxonomy machine learning methods for considers these problems by analyzing 77 chosen research works. The investigates context cybersecurity, including algorithm classification into numerous categories. Furthermore, was used evaluate most recent analysis. also examines obstacles associated concerns encountered potential remedies. Finally, address related issues would motivate researchers their future work, an empirical study utilized assess several algorithms.