Application Research of Optimized FCE Method in Information Security Risk Evaluation Model

Contraposing to the features of information system security risk in information incompleteness and conception uncertainty this article establishes a more comprehensive model for risk evaluation based on related analysis on risk factors. It integrated clustering method and FCE in fuzzy mathematics to quantify objective evaluation results of information security risk. Then the rule of “one man one vote” is introduced to explain fuzzy rule knowledge of experts marks. For each risk factor weight we introduce entropy index computation to over come the object effect caused by direct evaluation by experts, to achieve more scientific and rational evaluations. Illustrated by analysis and evaluation of the information security management system of certain power grid enterprise, the effectiveness and feasibility of improved FCE proposed in this article is verified.