A Network Security Risk Assessment Method Based on Fuzzy Bayesian

Abstract

The invention discloses a network security risk assessment method based on fuzzy Bayes. The invention provides an assessment level credibility algorithm according to a European spatial vector projection thought; the algorithm synthesizes opinions of many specialists and handles a condition that many assessment results are given by the specialists for uncertainty, and then the algorithm carries out fuzzy processing on the assessment results through a Gaussian membership function, and lastly, the algorithm solves the risk faced by a tested information system through combination with an inference algorithm of a Bayes network model. According to the method, the objectivity and the effectiveness of the assessment results can be enhanced, so that a more reasonable and effective basis is provided for the subsequent risk control and management.

Description

technical field [0001] The invention relates to a security risk assessment method, in particular to a fuzzy Bayesian network security risk assessment method based on orthogonal projection decomposition of reliability vectors, belonging to the field of network technology. Background technique [0002] With the development of Internet technology and the continuous innovation of network attack technology, many security issues brought by the network have become the focus of attention. As one of the important contents of information security work, information security risk assessment can only be as objectively and effectively as possible Only by identifying and quantifying risks can we ensure subsequent prevention and resolution of risks and keep them within an acceptable range. [0003] Commonly used information security risk assessment methods can be roughly divided into three categories: quantitative assessment methods, qualitative assessment methods and comprehensive assessme...

AI Technical Summary

Problems solved by technology

[0005] In the process of information security risk assessment, if there are many experts who evaluate each risk influencing factor and give multiple evaluation results due to their own uncertainties, the diversity and uncertainty of the evaluation results However, existing methods often cannot comprehensively deal with it well, and the objectivity of the obtained results needs to be improved.

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