Android malware detection based on permissions

In this paper, we propose a permission-based malware detection framework for Android platform. The proposed framework uses PCA(Principal Component Analysis) algorithm for features selection after permissions extracted, and applies SVM(support vector machine) methods to classify the collected data as benign or malicious in the process of detection. The simulation experimental results suggest that this proposed detection framework is effective in detecting unknown malware, and compared with traditional antivirus software, it can detect unknown malware effectively and immediately without updating the newest malware sample library in time. It also illustrates that using permissions features alone with machine learning methods can achieve good detection result.