Malware Analysis With Machine Learning

Abstract

Malware attacks are growing years after years because of increasing android, IOT along with traditional computing devices. To protect all these devices malware analysis is necessary so that interest of the organizations and individuals can be protected. There are different approaches of malware analysis like static, dynamic and heuristic. As the technology is advancing malware authors also use the advanced malware attacking techniques like obfuscation and packing techniques, which cannot be detect by signature based on static approaches. To overcome all these problems behavior of malware must be analyzed using dynamic approaches. Now a days malware author using some more advanced evasion techniques in which malware suspends its malicious behavior after detecting virtual environment. So, evasion techniques give a new challenge to malware analysis because even dynamic approach some time fails to detect and analyze the malwares.