Novel interval type-2 fuzzy logic controller for improving risk assessment model of cyber security

In this research paper, we have developed a novel interval type-2 fuzzy logic controller (IT2FLC) for improving risk assessment model for cyber security. The proposed IT2FIS implements this model to gain the total risk for such cyber security system which is combined with three sub models as a) Overall Capabilities, which is controlled by Capabilities, Intent, Targeting, b) Overall Likelihood, which depends on Vulnerability, Overall Capabilities and finally c) risk, which is measured by Overall Likelihood, Impact. Combining these three sub models, we have formulated and optimized the total risk assessment for a cyber security. This approach will have an enhanced control to forecast the possibility of risk assessment of cyber security despite the uncertainty in the data and information of cyber security due to various risks caused by the impacts of criminal activities depending upon the types of the offence, the victim and origin of the effects of the cyber crime. Finally, validity of the proposed model is discussed with the help of statistical analysis, Adaptive neuro-fuzzy inference system (ANFIS) and Multiple Linear Regression (MLR).