An Android application maliciousness detection method based on application behaviors
A detection method and malicious technology, applied in the field of Android application detection, can solve problems such as difficult unknown application analysis, inability to learn complex information representation, difficult problems, etc., to achieve automatic classification learning, avoid path explosion problems, and reduce analysis time Effect
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[0019] The present invention provides a static analysis method for Android application behavior analysis. Aiming at the characteristics of the Android system, it uses Android application function call graphs and control flow graphs, and adopts reverse analysis and program slicing technology to extract malicious behaviors in Android applications. Finally, combined with the deep learning model, the behavior of Android applications is detected for maliciousness.
[0020] The principle of the present invention is: because malicious functions are usually hidden in legitimate function codes, the inherent multi-component and event-driven features of the Android system make the malicious function codes more fragmented and more concealed, which intensifies the analysis of malicious functions of Android applications. Difficulty. The present invention firstly uses static analysis technology to analyze the control flow and data flow of the Dalvik executable file (dex file) of the Android app...
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