Support vector machines and malware detectionJournal of Computer Virology and hacking Techniques (2016)
In this research, we test three advanced malware scoring techniques that have shown promise in previous research, namely, Hidden Markov Models, Simple Substitution Distance, and Opcode Graph based detection. We then perform a careful robustness analysis by employing morphing strategies that cause each score to fail. We show that combining scores using a Support Vector Machine yields results that are significantly more robust than those obtained using any of the individual scores.
Citation InformationMark Stamp, Tanuvir Singh, Fabio Di Troia, Visaggio A. Corrado, et al.. "Support vector machines and malware detection" Journal of Computer Virology and hacking Techniques Vol. 12 Iss. 4 (2016) p. 203 - 212 ISSN: 2274-2042
Available at: http://works.bepress.com/mark_stamp/35/