基于IHS_LSSVR的网络安全态势预测方法  

Method of network security situation prediction based on IHS_LSSVR

作　　者：陈虹[1] 王飞[1] 肖振久[1,2] 孙丽娜[1] 

机构地区：[1]辽宁工程技术大学软件学院,辽宁葫芦岛125105 [2]中国传媒大学计算机学院,北京100024

出　　处：《计算机工程与应用》2014年第23期91-94,113,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61103199)

摘　　要：针对网络安全态势感知中的态势预测问题,提出一种基于IHS_LSSVR的网络安全态势预测方法。对和声搜索算法(HS)的原理进行了研究,在该基础上提出一种改进的和声搜索算法(IHS)。将最小二乘支持向量回归机(L-SSVR)嵌入到改进的和声搜索算法(IHS)的目标函数计算过程中,利用IHS算法的全局搜索能力来优化选取LSSV-R的参数,在一定程度上提升了LSSVR的学习能力和泛化能力。仿真实验表明,通过与已有的其他预测方法作对比,该方法具有更好的预测效果。To address the situation prediction problem in the network security situation awareness, this paper presents a prediction method of network security situation based on the algorithm of IHS_LSSVR. An improved Harmony Search （IHS）algorithm is proposed since the principle of the Harmony Search（HS）algorithm is studied. This method embeds the Least Squares Support Vector machine for Regression（LSSVR）in the process of the objective function calculation of the improved harmony search algorithm, and takes advantage of the global searching ability of the IHS algorithm to opti-mize the parameters of the LSSVR. To some extent, this enhances the learning ability and generalization ability of the LSSVR. Simulation experiments show that this method has better prediction affection in comparison with other existing prediction methods.

关 键 词：和声搜索算法 最小二乘支持向量回归机 参数优化 网络安全态势预测 

分 类 号：TP393.08[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]