Yue Li1, Guangquan Xu2,3, Hequn Xian1,*, Longlong Rao3, Jiangang Shi4,*
Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 637-647, 2019, DOI:10.31209/2019.100000118
Abstract In order to prevent the spread of Android malware and protect privacy
information from being compromised, this study proposes a novel multidimensional hybrid features extraction and analysis method for Android malware
detection. This method is based primarily on a multidimensional hybrid features
vector by extracting the information of permission requests, API calls, and
runtime behaviors. The innovation of this study is to extract greater amounts of
static and dynamic features information and combine them, that renders the
features vector for training completer and more comprehensive. In addition, the
feature selection algorithm is used to further optimize the extracted information
to… More >
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