Static Anomaly Detection Framework for Android-based Mobile Phones

With the rapid development of wireless communication, mobile network, and embedded system technologies, android-based mobile devices show a number of useful functions and then they are attacked by hackers for obtaining some useful information. In this paper, an efficient static anomaly detection framework is shown for android-based mobile phones to improve their security. The proposed framework uses support vector machine to perform the anomaly detection and exploits the cloud computing platform to reduce the impact on android-based mobile phones. Experimental results show that the proposed framework is better than existing anomaly detection frameworks in terms of the detection precision and the detection time.