基于和声搜索算法和相关向量机的网络安全态势预测方法  

Network security situation prediction method based on harmony search algorithm and relevance vector machine

作　　者：李洁[1] 张兆薇 

机构地区：[1]昆明理工大学质量发展研究院,昆明650093

出　　处：《计算机应用》2016年第1期199-202,232,共5页journal of Computer Applications

基　　金：云南省教育厅科学研究基金资助项目(2014Y081);昆明理工大学人才培养项目基金资助项目(KKSY201458053)~~

摘　　要：针对当前网络安全时变性、非线性、预测评估难的现状,提出一种基于和声搜索算法和相关向量机(HSRVM)的网络安全态势预测方法,以弥补现有预测方法在预测精度方面的不足。在预测过程中,首先对网络安全态势样本集进行归一化处理和相空间重构;然后,通过利用和声搜索(HS)算法搜索相关向量机(RVM)最优的超参数,以得到预测精度和速度都得到提升的网络安全态势预测模型;最后,采用Wilcoxon符号秩检验验证模型预测性能之间的差异性。仿真实例表明,所提预测方法的平均绝对百分误差(MAPE)和均方根误差(RMSE)分别为0.495 75和0.020 96,预测性能优于改进和声搜索(IHS)算法优化的正则极速学习机(RELM)预测模型和PSO算法优化的支持向量机回归(PSO-SVR)模型,Wilcoxon符号秩检验结果显示预测性能之间具有显著的差异性。所提预测方法能够较为精确描述网络安全态势变化规律,有利于网络管理者及时掌握网络安全态势变化趋势。To deal with the time-varying and nonlinear properties of network security and its difficulty in prediction assessment, a network security situation prediction method based on Harmony Search algorithm and Relevance Vector Machine（ HS-RVM） was proposed to offset the prediction accuracy drawbacks of existing prediction methods. In the prediction process,network security situation samples were firstly normalized and phase space was reconstructed; then, Harmony Search（ HS）algorithm was adopted to find out the optimal Relevance Vector Machine（ RVM） hyper parameters to build the network security situation prediction model with improved prediction accuracy and velocity; finally, Wilcoxon signed rank tests were used to testify the difference of prediction performance. The simulation cases indicate that the Mean Absolute Percentage Error（ MAPE） and the Root-Mean-Square Error（ RMSE） of the proposed prediction method are 0. 495 75 and 0. 020 96 respectively,with a better prediction performance than the Improved Harmony Search（ IHS） algorithm and Regularized Extreme Learning Machine（ IHS-RELM） prediction model and PSO and Support Vector machine for Regression（ PSO-SVR） prediction model.The outcome of Wilcoxon signed rank tests show there is a significant difference. The proposed method is capable to depict the changing rules of network security situation relatively, which is helpful for network administrators to control the changing tendency of network security situation in time.

关 键 词：和声搜索算法 相关向量机 网络安全态势 Wilcoxon符号秩检验 预测 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] TP18[自动化与计算机技术—计算机科学与技术]