基于遗传算法的网络安全态势感知研究

Research on network security situation awareness based on genetic algorithm

摘要:

对网络安全态势准确感知能实现对网络攻击的提前拦截和防范,针对传统的匹配检测方法对网络安全态势预测的精度不好的问题,提出一种基于遗传算法的网络安全态势感知模型,首先构建复杂网络环境下的病毒入侵的安全状态分布模型,进行网络安全态势的特征信息提取,然后采用遗传算法对提取的病毒入侵信息流进行相关性检测,实现安全态势预测和准确感知。仿真实验结果表明,该方法进行网络病毒入侵的准确检测概率较高,对安全态势预测的精度较高,保障了网络安全。

Abstract:

The network security situation can realize accurate perception of network attacks in advance to intercept and prevention, aiming at matching the traditional detection method of network security situation prediction accuracy is not good. A network security situation awareness model is proposed based on genetic algorithm, the security state distribution model first structure virus built under complex network environment the extraction of feature information of network security situation, then genetic algorithm is used to extract the virus information flow correlation detection, security situation prediction and accurate perception. Finally, the simulation results show that the proposed method has a high probability of accurate detection of network virus invasion, high accuracy of the security situation prediction, and ensure the network security.