Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review

Abstract

In recent years, the global pervasiveness of smartphones has prompted the development of millions of free and commercially available applications. These applications allow users to perform various activities, such as communicating, gaming, and completing financial and educational tasks. These commonly used devices often store sensitive private information and, consequently, have been increasingly targeted by harmful malicious software. This paper focuses on the concepts and risks associated with malware, and reviews current approaches and mechanisms used to detect malware with respect to their methodology, associated datasets, and evaluation metrics.

Keywords

• Smartphone
• intrusion detection
• mobile malware
• android devices
• machine learning