Current state-of-the-art Android static analysis tools avoid handling native method invocation. However, Recent research and our own statistics show that native payloads are commonly used in both benign and malicious apps. Among those methods, nearly all of them only consider the Java byte-code as the target to detect malicious behaviors. Recently, various approaches have been introduced to detect Android malware, the majority of these are either based on the Manifest File features or the structural information, such as control flow graph and API calls. It is arguably one of the most viral problems on mobile platforms. Download a PDF of the paper titled Android-COCO: Android Malware Detection with Graph Neural Network for Byte- and Native-Code, by Peng Xu Download PDF Abstract:With the popularity of Android growing exponentially, the amount of malware has significantly exploded.
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