支持向量机的智能信息安全风险评估模型

摘要

为了提高信息安全风险评估准确性,提出一种支持向量机的信息安全风险评估模型.首先通过模糊系统对风险评价指标进行预处理,然后将数据输入到支持向量机进行学习,并通过蚁群算法对支持向量机参数进行优化,建立智能化的信息安全风险评估模型,最后通过仿真实验对模型性能进行验证.仿真结果表明,支持向量机提高了信息安全风险评估的准确性,克服传统风险评估模型的缺陷,是一种性能优异的信息安全风险评估模型.%In order to improve the accuracy of information security risk assessment,we put forward an information security risk assessment model which is based on support vector machine.First,the risk evaluation indexes are pre-treated by fuzzy system,and then the data is inputted to support vector machine for learning,the ant colony is used to optimise the parameters of support vector machine and an intelligent information security risk assessment model is established; finally the model performance is verified by the simulation experiment.Simulation results show that the support vector machine improves the accuracy of information security risk assessment,overcomes the defect of traditional risk assessment models,and is an information security risk assessment model with excellent performance.