A Large-Scale Investigation to Identify the Pattern of Permissions in Obfuscated Android Malwares

Abstract

This paper represents a simulation-based investigation of permissions in obfuscated android malware. Android malware detection has become a challenging and emerging area to research in information security because of the rapid growth of android based smartphone users. To detect malwares in android, permissions to access the functionality of android devices play an important role. Researchers now can easily detect the android malwares whose patterns have already been identified. However, recently attackers started to use obfuscation techniques to make the malwares unintelligible. For that reason, it’s necessary to identify the pattern used by attackers to obfuscate the malwares. In this paper, a large-scale investigation has been performed by developing python scripts to extract the pattern of permissions from an obfuscated malwares dataset named Android PRAGuard Dataset. Finally, the patterns in a matrix form has been found and stored in a Comma Separated Values (CSV) file which will lead to the fundamental basis of detecting the obfuscated malwares.