Two Phase Static Analysis Technique for Android Malware Detection
Priyadarshani M. Kate, Sunita Dhavale · 2015
The growing popularity of Android based smart phones has greatly fuelled the spread of android malware. Further, these malwares are evolving rapidly to escape from traditional signature-based detection methods. Hence, there is a serious need to develop effective android malware detection techniques. In this paper, we propose two phase static android malware analysis scheme using bloom filters. The Phase I involves two different bloom filters that classify a given sample into malware or benign class based on permission feature set only. The evaded malicious samples from Phase I are further analyzed by Phase II consisting Naïve Bayes Classifier using permission and code based mixed feature set. Inclusion of Phase I classification makes the technique computationally less intensive; while addition of the Phase II classification improves the overall accuracy of the proposed model. Experimental results indicate both detection accuracy and computational efficiency of the proposed technique.