Mobile Malware Classification based on Phylogenetics

Abstract

Security researchers and practitioners face many challenges in mitigating mobile malware attacks against smartphones. Ranges of techniques have been developed by different developers to ensure that smartphones remain free from such attacks. However, we still lack efficient techniques to mitigate mobile malware attacks, especially for the iOS platform. Hence, this paper presents mobile malware classifications based on phylogenetics that can be used for mobile malware detection with regard to the iOS platform. Phylogenetics have been used as the basis concept associated with forming a mobile malware classification based on similar malware behavior, vulnerability exploitation and mobile phone surveillance features that originate from the same family of specific malware practices. A mobile malware classification based on the phylogenetic concept and on mathematical formulations has been developed for this purpose, and proof of the concept has been sought to support this new classification. This research was conducted in a controlled lab environment using open source tools and by applying dynamic analysis. Consequently, this paper can be used as reference for other researchers with the same interest in future.