摘要
为了有效判断用户行为的信任度,提升电力营商环境安全性与服务效果,设计了一种电力营商环境用户行为信任度自适应判断系统。利用k-means算法挖掘实体层提供的用户数据与交互数据,获取用户行为习惯数据;通过多维综合度量法,计算营商环境的表现信任度、内部属性信任度、认证信任度,获取综合环境信任度;在长短期记忆网络内输入用户行为习惯数据,输出用户历史行为信任度,自适应判断用户是否具备访问权限。实验证明,该系统可精准挖掘用户行为习惯数据,有效评估用户行为信任度。
In order to effectively judge the user behavior trust and improve the security and service effect of power business environment,an adaptive judgment system of user behavior trust in power business environment is designed.The k-means algorithm is used to mine the user data and interaction data provided by the entity layer to obtain the user behavior habit data.Through the multi-dimensional comprehensive measurement method,the performance trust,internal attribute trust and authentication trust of the business environment are calculated to obtain the comprehensive environment trust.The user behavior habit data is input to the long-term and short-term memory network,the user’s historical behavior trust is output,and the system can adaptively judge whether the user has access rights.Experiments show that the system can accurately mine user behavior habit data and effectively evaluate user behavior trust.
作者
黄鑫磊
王海龙
符倍源
耿万梅
HUANG Xinlei;WANG Hailong;FU Beiyuan;GENG Wanmei(Marketing Service Center of State Grid Xinjiang Electric Power Co.,Ltd.,Urumqi 830013,China)
出处
《微型电脑应用》
2024年第4期140-143,148,共5页
Microcomputer Applications
