基于自适应灰色维尔斯模型的C4ISR安全态势预测方法

Security Situation Forecasting Method of C4ISR Based on Adaptive Gray Verhulst Model

针对指挥信息系统中安全事件突然而不确定,传统方式难以准确预测网络安全态势的问题,提出了一种新型的自适应灰色Verhulst指挥信息系统安全态势预测方法.该方法考虑网络入侵攻击的本质和传统灰色Verhulst模型的缺点,建立了可调整生成序列的新型自适应灰色Verhulst模型,采用梯形规则和辛普森1/3规则的组合方法获得灰色微分方程中的背景值,从而对网络状态进行预测.利用基准数据集DARPA 1999和2000对所提方法进行验证,实验结果表明,与GM(1,1)和传统灰色Verhulst相比,所提算法具有更高的网络安全状况预测精度.

A new prediction method of adaptive gray Verhulst command information system security situation is proposed for the problem that the security event is unexpected and uncertain in the command information system and the traditional way is difficult to predict the network security situation accurately.This paper takes into account the nature of the network intrusion attack and the shortcomings of the traditional gray Verhulst model and establish A new adaptive gray Verhulst model with adjustable generation sequence.The background value of the gray differential equation is obtained from the combination of the trapezoidal rule and the Simpson 1/3 rule,so as to predict the network state.Finally,the proposed method is validated using the reference data set DARPA 1999 and2000.The experimental results show that compared with GM（1,1）and traditional gray Verhulst,the proposed algorithm has higher accuracy of network security prediction.