An Effective Machine Learning-Based File Malware Detection—A Survey

Abstract

The objective of this paper is to enable computers to learn on their own, identify malicious activities, increase scanner efficiency and sensitivity. The machine learning algorithm enables the identification of patterns in observed data, the development of models that explains the world and the prediction of things without explicitly preprogrammed rules and models. There have been huge research interests in the cybersecurity industry as well as in universities in the subjects of how to effectively block malicious documentation without a sign of slowing down. The main aim of the paper is to investigate the efficiency of large files and increase sensitivity in malware detection.