Huizhong Sun1, Guosheng Xu1,*, Zhimin Wu2, Ruijie Quan3
Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 585-600, 2022, DOI:10.32604/iasc.2022.023874
Abstract With the rapid development of Android devices, Android is currently one of the most popular mobile operating systems. However, it is also believed to be an entry point of many attack vectors. The existing Android malware detection method does not fare well when dealing with complex and intelligent malware applications, especially those based on feature detection systems which have become increasingly elusive. Therefore, we propose a novel feature selection algorithm called frequency differential selection (FDS) and weight measurement for Android malware detection. The purpose is to solve the shortcomings of the existing feature selection algorithms in detection and to filter… More >
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