分布式环境下用户网络信息安全性检测仿真

摘要

The security detection of user network information in distributed environment based on fuzzy support vector machine (FSVM) is studied.Firstly,the adaptive weight for the maximum of gradient of user network information is carried out.Then,directivity weight vector of network information connection of output user is obtained,and directivity beam cluster of ontology characteristic of user requirement integrated with FSVM is achieved.Finally,the farthest distance of FSVM class-center is used as measurement to define member function.According to that,the security detection is completed.Experimental results show that the method can improve efficiency of security detection effectively.%分布式网络环境下对用户网络信息安全性检测,能够真正解决网络安全问题.对网络的安全性进行检测,需要根据网络本体特征得到向量机类中心最远的距离,定义隶属度函数,完成对网络信息安全性检测.传统方法结合支持向量机理论对信息属性值进行划分聚类,最后将划分聚类结果输出,但忽略了建立隶属度函数,导致检测结果不准确.为解决上述问题,提出基于模糊支持向量机(FSVM)理论的分布式环境下用户网络信息安全检测方法.对用户网络信息梯度最大值进行自适应加权处理,得到输出用户网络信息关联指向性加权向量,结合模糊支持向量机理论实现用户需求本体特征指向性波束聚类,以模糊支持向量机类中心最远的距离作为度量定义隶属度函数,并以此为依据完成分布式环境下用户网络信息安全检测.实验结果表明,所提方法能够有效提升分布式环境下用户网络信息安全检测效率,且检测效果较好.