Android Malware Identification and Detection using Deep Learning
R. Poorvadevi, N.Bhavya Keerthi, N.Venkata Lakshmi · 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) · 2022
For Android malware detection, dynamic and static analysis technologies and constructs a hybrid deep learning model based on Support Vector Machine(SVM) and Random forest Static features with strong anti-obfuscation capabilities have been included to cope with obfuscation technology, and To improve the Android malware feature set, the dynamic properties of the application software at runtime are retrieved. A hybrid deep learning model employing Support Vector Machine(SVM) and Random Forest is used to train the model based on the characteristics of static and dynamic features, and the model's detection ability is proved through comparative tests.