Android Malware Detection Based on Deep Learning: Achievements and Challenges

Abstract

With the prosperous of Android applications, Android malware has been scattered everywhere, which raises the serious security risk to users. On the other hand, the rapid developing of deep learning fires the combat between the two sides of malware detection. Inducing deep learning technologies into Android malware detection becomes the hottest topic of society. This paper summarizes the existing achievements of malware detection from four aspects: Data collection, feature construction, network structure and detection performance. Finally, the current limitations and facing challenges followed by the future researches are discussed.