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Android-SEM: Generative Adversarial Network for Android Malware Semantic Enhancement Model Based on Transfer Learning
2022
Electronics
Currently, among the millions of Android applications, there exist numerous malicious programs that pose significant threats to people's security and privacy. Therefore, it is imperative to develop approaches for detecting Android malware. Recently developed malware detection methods usually rely on various features, such as application programming interface (API) sequences, images, and permissions, thereby ignoring the importance of source code and the associated comments, which are not
doi:10.3390/electronics11050672
fatcat:2hpovbmmg5h4liznlu36klhlpe