A Behavior-based Mobile Malware Detection Model in Software-Defined Networking

In recent years, the number of mobile devices is increasing rapidly. Meanwhile, the amount of malicious software is rising almost exponentially, alongside the diversity and complexity of malware. The flexibility of Software-Defined Networking (SDN) provides an opportunity to develop a malware detection model in more efficient and flexible manner. In this paper, we propose a network behavior-based malware detection system for mobile devices in SDN which is composed of three algorithms including IP Blacklist, Connection Success Ratio, Connection Rate algorithms. The experiment demonstrates that the proposed system is feasible and effective.