A Comprehensive Review on Android Malware Detection: Techniques, Challenges, and Future Directions
G. Srinivas, M. V. Rajesh · 2025
The proliferation of Android devices has made the platform a primary target for malware attacks, posing significant security threats to users and organizations. This survey examines the evolving landscape of malware detection, with a focus on Android-specific challenges and solutions. It reviews general malware detection techniques to establish a foundational understanding. Android-specific approaches, such as static, dynamic, hybrid, and image-based techniques, are explored, alongside the transformative role of machine learning and deep learning in enhancing detection accuracy. Key challenges, including dataset limitations and privacy concerns, are discussed. Finally, the survey identifies open research directions and emphasizes the need for robust, adaptive, and privacy-preserving solutions to secure the Android ecosystem. This comprehensive survey aims to provide valuable insights for researchers and practitioners into the current state and future prospects of Android malware detection.