An Android Malware Detection Approach Using Weight-Adjusted Deep Learning
Wenjia Li, Zi Wang, Juecong Cai, Cheng Sihua · 2018 International Conference on Computing, Networking and Communications (ICNC) · 2018
Smartphones recently become an indispensable part of our daily lives. Among various smartphones, Android-based smartphone has become a most popular choice because of the large amount of Android applications (apps) which are developed to make user experience more convenient with rich features. To cope with malicious applications (malwares) which severely threaten the security of Android smartphones, we propose an Android malware characterization and identification approach that uses deep learning algorithm to address the urgent need for malware detection. Extensive experimental results show that our approach achieves over 90% accuracy with only 237 features.