可信网络攻击形式智能预测方法仿真

发布时间：2018-06-04 13:16

本文选题：可信网络 + 攻击形式　；参考：《计算机仿真》2017年10期

【摘要】：为了保障可信网络的稳定运行,需要进行可信网络攻击形式智能预测方法的研究。但是采用当前方法进行攻击预测时,无法预测出攻击者实际的攻击形式,存在攻击预测误差大的问题。为解决上述问题,提出一种基于卡尔曼波的可信网络攻击形式智能预测方法。上述方法先利用灰色关联理论对基于攻击形式的报警事件进行分类,在每个大类中划分出若干个基于攻击形式的子类,得到攻击者每次攻击的基于攻击形式的复合攻击表述,对网络攻击各因子序列的灰关联度系数进行分布映射,计算主机的攻击风险值,组建基于卡尔曼波的可信网络攻击形式状态表述方程,完成对可信网络攻击形式智能预测。仿真证明,所提方法预测精度高,为保障可信网络的稳定运行奠定了基础。
[Abstract]:In order to guarantee the stable operation of trusted network, it is necessary to study the intelligent prediction method of trusted network attack form. However, when the current method is used to predict the attack, it is impossible to predict the actual attack form of the attacker, and there is a problem that the prediction error of the attack is large. In order to solve the above problems, an intelligent prediction method of trusted network attack form based on Kalman wave is proposed. Firstly, the grey relational theory is used to classify the alarm events based on the form of attack, and several subclasses based on the form of attack are divided into several subclasses in each class, and the compound attack expression based on the form of attack is obtained for each attack. The grey correlation coefficient of each factor sequence of network attack is mapped, the attack risk value of host is calculated, the state expression equation of trusted network attack form based on Kalman wave is established, and the intelligent prediction of trusted network attack form is completed. Simulation results show that the proposed method has high prediction accuracy and lays a foundation for the stable operation of trusted networks.
【作者单位】：上海外国语大学贤达经济人文学院;
【分类号】：TP393.08

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