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Hunting Malicious Windows Commands with Multi Machine Learning Technologies

This study presents a framework to detect malicious windows commands by using both statistical and deep learning algorithms. Our method consists of two stages. In the first stage, malicious windows commands are identified using a benign profile with the Euclidean distance. In the second stage, we recognize the malicious part in the Windows commands by using Natural Language Processing and proposed a scoring mechanism. Finally, we used two real cases to verify our method's effectiveness in detecting malicious commands and malicious parts. We also verify that the factor affecting the precision, recall and demonstrated our approach was effective through experiments.