Enhancing the Detection of Metamorphic Malware using Deep Learning

Abstract

Malware is the name for a malicious variants. Malware models conatins code generated by cyberattackers, plan to cause distrupt to data and systems or to gain unauthorized access to a network. Malware have been enormously increasing in now a days. Majority of malware utilize obfuscation methods for avoidance and abstruse motive, but they conserve the purpose and malicious behaviour of native Rey. Attackers uses metamorphic techniques to build viruses that change their internal construction all bug. Malware signatures and behaviour samples acquire static and dynamic analysis that are ineffectual in recognising undetermine malwares.In general,these metamorphic viruses are very hard to detect. In this paper, we suggest HMM as a novel solution for metamorphic detection.