Dong-Wook Kim1, Gun-Yoon Shin1, Myung-Mook Han2, *
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1891-1904, 2020, DOI:10.32604/cmc.2020.010933
Abstract This study was conducted to enable prompt classification of malware, which
was becoming increasingly sophisticated. To do this, we analyzed the important features
of malware and the relative importance of selected features according to a learning model
to assess how those important features were identified. Initially, the analysis features
were extracted using Cuckoo Sandbox, an open-source malware analysis tool, then the
features were divided into five categories using the extracted information. The 804
extracted features were reduced by 70% after selecting only the most suitable ones for
malware classification using a learning model-based feature selection method called the
recursive feature… More >
Login
Register
