RobotDroid: A Lightweight Malware Detection Framework on Smartphones

Smartphones have been widely used in recent years due to their capabilities of communication and multimedia processing, thus they also become attack targets of malware. In this paper, a new software behavior signature based malware detection framework named RobotDroid using SVM active learning algorithm is proposed, active learning algorithm is very efficient in solving a small amount of labeled samples and unlabeled samples posed a lot of mixed sample training set classify problems, as a result, RobotDroid can detect kinds of malicious software and there variants effectively in runtime and it can self extend malware characteristics database dynamically.