Analysis of mobile malware based on user awareness

The number of mobile device malware has been increasing drastically last several years. When attempting to detect malware within a device, it is difficult to draw a clear line between malicious and normal activities. Even useful applications naturally result in data transfer from a mobile device to a remote server and a malware detection mechanism based solely on information flow might consider this as data leakage. Therefore one should also consider the surrounding context of an application to make a better decision on whether it is malicious or not. In this current research, a dynamic analysis approach is taken which monitors and measures the runtime behavior and logs from the mobile application. In particular, a concept of user awareness (UA) is proposed which represents a degree of intent with which an application tries to hide its activities from a user. This extended analysis measurement, combined with dataflow-based analysis, will help make a more accurate decision with less false positives.