NetLinX开放网络下异常权限配置挖掘算法

Abnormal permission configuration mining algorithm under NetLinX open network

针对传统异常权限配置挖掘算法在NetLinX开放网络下存在挖掘精度较差、挖掘效率低的问题,通过数据净化、会话与用户识别和路径补充过程对权限配置数据进行预处理,并对异常权限进行规则匹配,采用异常数据集定义对数据进行综合数据算法挖掘处理。在算法的起始阶段,应用OPTICS方法对原始集合中的密集数据进行聚类,并将松散数据集转换为异常种簇,持续分析处理直至完成挖掘。发现NetLinX开放网络下挖掘算法的挖掘精确度最高可达到95%,挖掘效率可达到90%;基于谱聚类的挖掘算法的挖掘精确度最高仅为87%,挖掘效率最高仅为66%。研究表明,NetLinX开放网络下异常权限配置挖掘算法能更有效地实现异常权限配置挖掘。

Mining algorithm for traditional abnormal permission configuration has poor mining accuracy,and low mining efficiency under NetLinX open web.Permission configuration data is thus preprocessed through the data cleansing,session identification process and path supplement,and the abnormal access rules are matched,integrated algorithm of data mining of the data processing is made by the abonormal data set difinitions.In the initial stage of the algorithm,the OPTICS method is applied to cluster the dense data in the original set,and the loose data set is transformed into the abnormal species cluster,which is continuously analyzed and processed until the mining is completed.It is found that the mining accuracy of the algorithm under NetLinX open network is up to 95%,while that of the algorithm based on spectral clustering is up to 87%.The mining efficiency of the mining algorithm under NetLinX open network can reach 90%,while that of the mining algorithm based on spectral clustering is only 66%.The research shows that the algorithm of mining abnormal permission configuration in NetLinX open network can realize the mining of abnormal permission configuration more effectively.