The method proposed in this paper, based on the TCN model, can effectively utilize bytecode image sequence features, improve the accuracy of detecting Android ...
Abstract: With the rapid increase in the number of Android malware, the image-based analysis method has become an effective way to defend against symmetric ...
Jun 16, 2021 · A novel detection method based on a lightweight convolutional neural network is presented in this study. It transforms Android malware classes.
The experimental results show that adding XML files is beneficial for Android malware detection. The detection accuracy of the TCN model is 95.44%, precision is ...
At present, the existing Android malware bytecode image detection method, based on a convolution neural network (CNN), relies on a single DEX file feature and ...
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A new technique to detect Android malware effectively based on converting malware binaries into images and applying machine learning techniques on those ...
Nov 14, 2024 · Research from Xinjiang University in the Area of Mathematics Published (Android Malware Detection Using TCN with Bytecode Image). Citation ...
This paper visualises Android malware into gray scale images and their image features will be extracted using GIST descriptor and compares using three ...
In this paper, we survey six APK to image conversion techniques and perform a comparative empirical analysis of these methods with respect to malware detection ...
Feb 16, 2024 · In addition, images plays a vital role in detecting obfuscated malware ... Android malware detection using tcn with bytecode image. Symmetry 13 ...