为有效监视网络安全态势变化和预防网络遭受大规模安全攻击,受人工免疫系统居发,提出了一种基于免疫优化原理的网络安全态势预测方法(NSSPAI)。该预测方法首先给出网络安全态势预测环境下抗原、抗体和亲和力的定义,以及用于挖掘态势预测模型的抗体优化算子的抽象数学模型;然后利用相空间重构理论分析网络安全态势时间序列,利用重构后的样本空间和免疫优化建模方法挖掘态势预测模型;最后利用该预测模型来预测未来的网络安全态势。实验结果表明,与基于遗传算法的预测方法相比,NSSPAI预测方法能够更为准确地预测网络安全态势,是一种有效预测网络安全态势的新方法。
To effectively monitor networks' security situation and prevent large-scale networks from being attacked, a novel network security situation prediction approach based on the immune optimization theory. (NSSPAI) is proposed. The NSSPAI works according to the steps described belows: firstly, it gives the definitions of antigen, antibody and affinity in the environment of network security situation prediction, and gives the mathematical models of some antibody optimizing operators for constructing a prediction model ; secondly, the time series of network security situation is analyzed by using the phase space reconstruction theory, and a prediction model is established by using the reconstructed sample space and the immune optimizing modeling method; lastly, the future network security situation is predicted by this model. The experimental results show that the NSSPAI can forecast the future network security situation more exactly than the genetic algorithm based prediction approach, and it is a new method for effective prediction of network security situation.