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Detecting file types using machine learning algorithms
(IEEE, 2019) Konaray, Serdar Korhan; Toprak, Aykut; Pek, Gamze Mat; Akçekoce, Hüseyin; Kılınç, Deniz
In this study, experiments have been carried out to analyze the file content and classify the type of file using machine learning algorithms. First a new benchmark dataset was created including popular file types used as malicious software. Then the proposed system was trained using different machine learning algorithms. The accuracy and runtime performance comparison of models were evaluated. As a result, the highest accuracy rate was obtained as 97.83% by XGBoost algorithm.