Android malware detection method based on combined algorithm - Hao CHEN; Sihan QING (Dianxin kexue)
In order to solve the problems in applicability and usability of today's static malware detection method, a detection system was implemented by using the optimal classifier selected by a combined algorithm as the core. Firstly, the reverse engineering was used to extract the software feature, then the preliminary results of the classifier was got by multi-stage screening. A classifier evaluation was presented based on minimum risk Bayes. Using the new one as the core, the optimal classifier results was got by assignment. Finally, an Android malware detection system prototype was realized using the optimal results as the core. Experimental results show that the analysis accuracy of the proposed detection system was 86.4%, and does not depend on characteristics of the malicious code.