Android Malware Detection using Large-scale Network Representation Learning

Understand

With the growth of mobile devices and applications, the number of malicious software, or malware, is rapidly increasing in recent years, which calls for the development of advanced and effective malware detection approaches.

• Traditional methods such as signature-based ones cannot defend users from an increasing number of new types of malware or rapid malware behavior changes.
• In this paper, we propose a new Android malware detection approach based on deep learning and static analysis.
• Instead of using Application Programming Interfaces (APIs) only, we further analyze the source code of Android applications and create their higher-level graphical semantics, which makes it harder for attackers to evade detection.