基于量子遗传算法的网络安全态势感知研究

Research on Network Security Situation Awareness Based on Quantum Genetic Algorithm

基于当前网络状态分析,有利于指导以后的安全态势估计,为了提高网络安全态势感知的主动性和可靠性,提出基于量子遗传算法的网络安全态势感知方法。根据属性的相似度函数计算网络态势信息的相似度,并由报警相似度函数求解出两个报警信息的相似关系。建立对复杂环境下病毒攻击的网络安全态势模型,采用信号处理方法对网络安全态势感知优化。通过量子遗传算法,对网络病毒的交叉点进行区域匹配设置,同时检测病毒入侵的网络信息流,对网络安全态势进行更加精确地感知。基于CICIDS2017进行仿真,实验结果表明,提出的算法得到的安全态势预测结果具有更高的精确性和稳定性,能够有效地提高网络环境的安全性。

Based on the current network state analysis,it is helpful to guide the future security situation assessment.In order to improve the initiative and reliability of network security situation awareness,a network security situation awareness method based on a quantum genetic algorithm is proposed.Firstly,the similarity of network situation information was calculated according to the similarity function of attributes,and the similarity relationship of two alarm information was solved by the alarm similarity function.Then,the network security situation model of the virus attack in a complex environment was established,and the signal processing method was used to optimize the network security situation awareness.Finally,through the quantum genetic algorithm,the cross point of the network virus was matched and set,and the network information flow of virus intrusion was detected,so that the network security situation could be more accurately perceived.Based on CICIDS2017,the simulation results show that the security situation prediction results obtained by the proposed algorithm have higher accuracy and stability,and can effectively improve the security of the network environment.