Dynamic detection method for Android terminal malware based on Native layer

The current traditional malware detection methods mainly obtain the characteristics of malware by analyzing the static file structure and binary byte code of the software, which leads to poor detection due to the lack of fusion processing of the characteristics. In this regard, we propose a dynamic detection method for Android terminal malware based on Native layer. The APK installation package of the Android application is parsed, and the dex file and Native library file are fused and mapped into a three-channel visual RGB color image, and the malware features are extracted and fused to achieve dynamic detection of malware. In the experiments, the detection performance of the proposed method is verified. The experimental results show that the proposed method has a larger ROC curve area and has a more desirable detection performance when malware is detected by the proposed method.