Decision Support Method and Risk Analysis Based on Merged-Cyber Security Risk Management

The Cyber Security Risk Management is the essential part in today’s business because of quickly changing landscape of threat and presence of developing the cyber-attacks. Developed numerous researches which aim to built systematic process in risk assessment and management. This challenge developed particularly in content of difficult infrastructures, from attacks has involved from technic to social technic and protect against them required that contextual data. Though, the previous researches have restricted input from the intelligence properties of threat and developing the attack trends, resulted in restricted contextual data relevance to the risks of cyber security. In this research, developed Merged Cyber Security Risk Management (m-CSRM) method which responded to the difficulty through helping the systematic identity of critical assets by utilize of decision support method developed on fuzzy set mechanism through predict the risk types by Machine Learning (ML) methos and that is processed through automated tool. The proposed m-CSRM method attained highest success rate of 82.13% which is efficient than other existing methods.