Method of Detecting Malware Through Analysis of Opcodes Frequency with Machine Learning Technique

摘要

As the evolution of malware, vast damages are occurred in various industry fields. For this reason, research on malware detection has conducted actively. To improve the security of the network, SDN Quarantined Network (SQN) has been proposed. In this paper, we developed one of malware detection modules in first quarantine station in SQN by using the fact that benign and malicious files have different opcode frequency. And we applied machine learning technique as different way compare to conventional method. we verified that our module is valuable as one of detection modules and our final aim is to mount this module on the SQN system. Therefore, it would be possible more accurate inspection for new type of security attack with multiple detection modules.