期刊名称：International Journal of Network Security & Its Applications
印刷版ISSN：0975-2307
电子版ISSN：0974-9330
出版年度：2019
卷号：11
期号：1
页码：1-14
DOI：10.5121/ijnsa.2019.11101
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This research paper is focused on the issue of mobile application malware detection by Reverse Engineering of Android java code and use of Machine Learning algorithms. The malicious software characteristics were identified based on a collected set of total number of 1958 applications (including 996 malware applications). During research a unique set of features was chosen, then three attribute selection algorithms and five classification algorithms (Random Forest, K Nearest Neighbors, SVM, Nave Bayes and Logistic Regression) were examined to choose algorithms that would provide the most effective rate of malware detection.
