摘要
当下如何从社交网络平台中自动准确地挖掘网络空间安全相关用户具有重要意义。在现有的基于社交关系的相似度算法基础上,结合基于动态交互信息的相似度算法,加权综合两种用户相似度算法,提出一种新的用户相似度算法,从而初步计算社交网络中网络空间安全相似用户。再通过基于机器学习的用户分类算法,从网络空间安全相似用户中进一步准确地检测网络空间安全领域的用户,最终构建社交网络的网络空间安全用户挖掘模型。
It is important to automatically and accurately to excavate cyber security users from social networking platforms.First,in order to gain the similarity cybersecurity users from social network approximately,constructs a new user similarity calculation model based on users’social relations and dynamic interaction information through presenting a comprehensive similarity measurement method by weighting.Then uses user classification methods based on machine learning algorithms to detect the cybersecurity users more accurately from the previous simi⁃lar users,and finally constructs the cybersecurity users extracting model.
作者
赵翠镕
黄建军
孙鹏
方勇
祝鹏程
ZHAO Cui-rong;HUANG Jian-jun;SUN Peng;FANG Yong;ZHU Peng-cheng(College of Cybersecurity,Sichuan University,Chengdu 610207)
出处
《现代计算机》
2020年第12期4-8,14,共6页
Modern Computer
基金
国家重点研发计划资助(No.2016YFE0206700、2018YFB0804503)。
关键词
社交网络
动态交互信息
用户分类
网络空间安全
用户挖掘模型
Social Network
Dynamic Interaction Information
User Classification
Cybersecurity
User Extracting Model