Mobile Malware Classification based on Phylogenetics
Madihah Mohd Saudi1, Sazali Sukardi2, Amirul Syauqi Mohamad Syafiq3, Azuan Ahmad4, Muhammad ‘Afif Husainiamer5
1Madihah Mohd Saudi*, Cybersecurity and System Research Unit, Islamic Science Institute, University Sains Islam Malaysia, Nilai, Malaysia.
2Sazali Sukardi, Cybersecurity Malaysia, Cyberjaya, Malaysia
3Amirul Syauqi Mohamad Syafiq, Faculty of Science and Technology, University Sains Islam Malaysia, Nilai, Malaysia.
4Azuan Ahmad, Cybersecurity and System Research Unit, Islamic Science Institute, University Sains Islam Malaysia, Nilai, Malaysia.
5Muhammad ‘Afif Husainiamer, Faculty of Science and Technology, University Sains Islam Malaysia, Nilai, Malaysia.
Manuscript received on September 02, 2019. | Revised Manuscript received on September 22, 2019. | Manuscript published on October 30, 2019. | PP: 3661-3665 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2710109119/2019©BEIESP | DOI: 10.35940/ijeat.A2710.109119
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: IOS, Malware Classification, Mathematical Formulation, Mobile Malware, Phylogenetic, Surveillance Feature, Vulnerability Exploitation.