Software Malicious Behavior Analysis Model based on System Call and Function Interface

Malware issue puzzles software users. Under the development of Internet, software technology has been involved in all parts of life such as Robot Control Software. There have been many methods to detect malicious Android applications. However, most of these are single behavior analysis models. In order to better detect the malicious behavior for more fields, we propose a malicious behavior analysis model based on system call and function interface with machine learning algorithm training. To clear the analysis model, we discuss the reasonable feature selection, data collection and analyze the implementation of static methods, dynamic methods and hybrid methods. In addition, we compare several important algorithm models to get the optimal model. Experimental result shows that our proposed optimal model has a higher accuracy than traditional way.