云计算环境下的网络安全估计模型态势仿真

摘要

In the cloud computing environment,the traditional method,which takes the terminal network monitoring method to estimate the network security,has low estimated accuracy for security situation and poor detection performance due to the high power attenuation of network communication channel terminal. A security estimation and trend prediction algorithm based on adaptive data classification and membership feature extraction of virus infection in cloud computing environment is proposed. The network security estimation model based on cloud computing environment is established,the adaptive data classification al⁃gorithm is adopted to carry out clustering evaluation for network attacks data,and the infection membership feature of virus at⁃tacks data is extracted to realize the network security situational prediction and virus attack detection. The simulation test results show that the algorithm has high virus data flow prediction accuracy,can realize network virus flow prediction and data detec⁃tion in different scenarios,and improve the ability of resisting the virus attacks in cloud computing environment.%在云计算环境下，传统方法采用终端网络监测方法进行网络安全估计，由于网络通信信道终端功率衰减性强，导致安全态势估计精度不高，检测性能不好。提出一种基于自适应数据分类和病毒感染隶属度特征提取的云计算环境下网络安全估计及态势预测算法。构建云计算环境下的网络安全估计模型，采用自适应数据分类算法对网络攻击信息数据进行聚类评估，提取网络攻击病毒数据的感染隶属度特征，实现网络安全态势预测和病毒攻击检测。仿真实验表明，该算法对病毒数据流预测精度较高，实现不同场景下的网络病毒流预测和数据检测，提高了云计算环境下网络抵御病毒攻击的能力。