Malware detection on Android smartphones using API class and machine learning
作者： Westyarian , Yusep Rosmansyah , Budiman Dabarsyah
DOI: 10.1109/ICEEI.2015.7352513
关键词: Cross-validation 、 Android (operating system) 、 Computer science 、 Software 、 Malware 、 Application programming interface 、 C4.5 algorithm 、 Artificial intelligence 、 Random forest 、 Support vector machine 、 Machine learning
摘要: This paper proposes a (new) method to detect malware in Android smartphones using API (application programming interface) classes. We use machine learning classify whether an application is benign or malware. Furthermore, we compare classification precision rate from learning. research uses 51 APIs package classes 16 and employs cross validation percentage split test Random Forest, J48, Support Vector Machine algorithms. 412 total samples (205 benign, 207 malware). obtain that the average 91.9%.
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