Data-Driven Android Malware Intelligence: A Survey

Abstract

Android has dominated the smartphone market and become the most popular mobile operating system. This rapidly increasing market share of Android has contributed to the boom of Android malware in numbers and in varieties. There exist many techniques which are proposed to accurately detect malware, e.g., software engineering-based techniques and machine learning (ML)-based techniques. In this paper, our main contributions are threefold: We reviewed the existing analysis techniques for Android malware detection; We focused on the code analysis based detection techniques under the ML frameworks; We gave the future research challenges and directions about Android malware analysis.