Abstract: 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 optimize 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.

Key words: Harmony Search algorithm（HS）, Least Squares Support Vector machine for Regression（LSSVR）, parameters optimization, network security situation prediction

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。

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