AntiMalDroid: An Efficient SVM-Based Malware Detection Framework for Android

Mobile handsets, especially smartphones, are becoming more open and general-purpose, thus they also become attack targets of malware. Threat of malicious software has become an important factor in the safety of smartphones. Android is the most popular open-source smartphone operating system and its permission declaration access control mechanisms can’t detect the behavior of malware. In this work, AntiMalDroid, a software behavior signature based malware detection framework using SVM algorithm is proposed, AntiMalDroid can detect malicious software and there variants effectively in runtime and extend malware characteristics database dynamically. Experimental results show that the approach has high detection rate and low rate of false positive and false negative, the power and performance impact on the original system can also be ignored.