Sharif Digital Repository

Android is a major target of attackers for malicious purposes due to its popularity. Despite obvious malicious functionality of Android malware, its analysis is a challenging task. Extracting and using features that discriminate malicious and benign behaviors in applications is essential for malware classification in using machine learning methods. In this paper, we propose a new feature in Android malware classification process which in combination with other proposed features, can discriminate malicious and benign behaviors with a good accuracy. Using components such as activities and services in Android applications' source code will lead to different flows on invoking between...