Machine learning aided Android malware classification

Another research paper titled "Machine learning aided Android malware classification" published in Computers & Electrical Engineering journal. Following is the paper abstract:

The widespread adoption of Android devices and their capability to access significant private and confidential information have resulted in these devices being targeted by malware developers. Existing Android malware analysis techniques can be broadly categorized into static and dynamic analysis. In this paper, we present two machine learning aided approaches for static analysis of Android malware. The first approach is based on permissions and the other is based on source code analysis utilizing a bag-of-words representation model. Our permission-based model is computationally inexpensive, and is implemented as the feature of OWASP Seraphimdroid Android app that can be obtained from Google Play Store. Our evaluations of both approaches indicate an F-score of 95.1% and F-measure of 89% for the source code-based classification and permission-based classification models, respectively.

For the full text please refer to: http://www.sciencedirect.com/science/article/pii/S0045790617303087

Ali Dehghantanha

Dr. AliDehghantanha (www.alid.info) has served for more than a decade in a variety of industrial and academic positions with leading players in Cyber-Security and E-Commerce. He has long history of working in different areas of computer security as security researcher, malware analyzer, penetration tester, security consultant, professional trainer, and university lecturer. Ali is imminently qualified in the field of cyber security; he has an EU Marie Curie post-doctoral fellowship in cyber forensics (the Marie Curie Fellowships are Europe’s most competitive and prestigious award), Ph.D in Security in Computing and a number of professional qualifications namely SANS-GIAC Exploit Researcher and Advanced Penetration Tester (GXPN), SANS-GIAC Reverse Engineering Malware (GREM), SANS-GIAC Certified Forensics Analyst (GCFA), CCFP (Certified Cyber Forensic Professional), CISSP (Certified Information Systems Security Professional), and CEH (Certified Ethical Hacker). Ali is a fellow of the UK Higher Education Academy (HEA) and served as a keynote speaker for a number of security conferences namely the International Conference on Information Security and Cyber Forensics (InfoSec2015) speaking about “Detection and analysis IoT Malwares" at Cape-Town, South Africa, keynote speaker at the International Conference on Information Security and Digital Forensics (ISDF2015) speaking on "Efficient Analysis of Malware Campaigns" at Kuala Lumpor, Malaysia and invited speaker for ISACA EuroCACS/ISRM 2015 speaking about "Finding the Needle in Internet of Everything Haystack" at Copenhagen, Denmark. In 2015, he was an invited speaker for ISACA North-West UK meeting and talked about "Strategic Cyber Threat Intelligence".  He was one of the lead editors for Elsevier book titled “Contemporary digital forensic investigations of cloud and mobile applications” and a guest editor for a special issue on “Internet of Things: Security and Forensics Trends and Challenges” in the Elsevier Future Generation Computer Systems journal, guest editor for a special issue on "Big Data Applications in Cyber Security and Threat Intelligence" in IEEE Transactions on Big Data.  Ali is the founder of annual “International Conference in Cyber-Security, Cyber Warfare and Digital Forensics (CyberSec)” and served as editor in chief for the International Journal of Cyber Security and Digital Forensics (IJCSDF) between Jan 2012 to Jan 2015!