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http://dx.doi.org/10.13089/JKIISC.2020.30.3.357

Advanced Feature Selection Method on Android Malware Detection by Machine Learning  

Boo, Joo-hun (Graduate School of Information Security, Korea University)
Lee, Kyung-ho (Graduate School of Information Security, Korea University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.30, no.3, 2020 , pp. 357-367 More about this Journal
Abstract
According to Symantec's 2018 internet security threat report, The number of new mobile malware variants increased by 54 percent in 2017, as compared to 2016. And last year, there were an average of 24,000 malicious mobile applications blocked each day. Existing signature-based technologies of malware detection have limitations. So, malware detection technique through machine learning is being researched to detect malware variant. However, even in the case of applying machine learning, if the proper features of the malware are not properly selected, the machine learning cannot be shown correctly. We are focusing on feature selection method to find the features of malware variant in this research.
Keywords
Android; Malware; Machine Learning; Feature Selection;
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Times Cited By KSCI : 2  (Citation Analysis)
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