CAJ | 학술논문

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。
재운계산배경하，전통방법채용종단망락감측방법진행망락안전고계，유우망락통신신도종단공솔쇠감성강，도치안전태세고계정도불고，검측성능불호。제출일충기우자괄응수거분류화병독감염대속도특정제취적운계산배경하망락안전고계급태세예측산법。구건운계산배경하적망락안전고계모형，채용자괄응수거분류산법대망락공격신식수거진행취류평고，제취망락공격병독수거적감염대속도특정，실현망락안전태세예측화병독공격검측。방진실험표명，해산법대병독수거류예측정도교고，실현불동장경하적망락병독류예측화수거검측，제고료운계산배경하망락저어병독공격적능력。
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.