信息工程大学学报2024，Vol.25Issue(3)：285-291,7.DOI:10.3969/j.issn.1671-0673.2024.03.006
基于链接预测匹配的动态社交机器人检测方法
Social Bot Detection for Dynamic Social Networks Based on Link Prediction
摘要
Abstract
The malicious social bots in online social networks threaten the information security and af-fect the credit system of social networks,and it is imperative to effectively detect bot accounts.To ad-dress the problem that existing bot detection methods are difficult to portray the dynamic link behavior in social graphs,a dynamic bot detection method based on link prediction is proposed in this paper.We build node link prediction models based on the known links of bots and human users respectively,to learn the difference between the link behavior of both types of nodes.Finally,the classification is achieved by examining the agreement of unknown node link behavior with respect to two types of link prediction models.On the Twitter dataset,the detection accuracy is significantly improved compared with the baseline method without using temporal data,which verifies the effectiveness of this method in using temporal data.关键词
社交网络/机器人检测/链接预测/图神经网络Key words
social networks/bot detection/link prediction/graph neural network分类
信息技术与安全科学引用本文复制引用
卢昊宇,刘峰,王博雅,谭磊,左宗..基于链接预测匹配的动态社交机器人检测方法[J].信息工程大学学报,2024,25(3):285-291,7.基金项目
国家自然科学基金(61872448,62002387,61772549,U1804263) （61872448,62002387,61772549,U1804263）
河南省重点研发专项(221111321200) （221111321200）
