基于粒子群算法优化最小二乘支持向量机的网络安全态势评估  

Network Security Situation Assessment Based on Particle Swarm Algorithm Optimizing Least Square Support Vector Machine

作　　者：黄东[1] 李长彬[1] 

机构地区：[1]钦州学院数学与计算机科学学院,广西钦州535000

出　　处：《信阳师范学院学报（自然科学版）》2016年第1期113-115,133,共4页Journal of Xinyang Normal University(Natural Science Edition)

基　　金：广西高校科学技术研究项目(2013YB259);广西高校科学技术研究重点项目(ZD2014137)

摘　　要：为了提高网络安全态势评估的准确性,提出一种基于最小二乘支持向量机和粒子群优化算法的网络安全态势评估模型.通过分析参数对最小二乘支持向量机性能的影响,并采用粒子群优化算法选择模型参数,建立网络安全态势评估模型,最后采用仿真对比实验测试模型的有效性和优越性.结果表明,本文模型获得理想的网络安全态势评估结果,可以为网络管理人员提供有价值的参考信息.In order to improve the assessment accuracy of network security situation, a network security situation assessment model was proposed based on particle swarm optimization（PSO） algorithm and least squares support vector machine. Firstly, the parameters on the performance of least squares support vector machine were analyzed, and secondly the parameters of least squares support vector machines were selected using the PSO algorithm, and the model of network security situation assessment was given. Finally the simulation experiment was used to test its validity and superiority. The results showed that the proposed model can obtain more ideal results of the network security situation assessment.

关 键 词：最小二乘支持向量机 网络安全 态势评估 模型参数 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]