四川大学学报（自然科学版）2024，Vol.61Issue(4)：37-46,10.DOI:10.19907/j.0490-6756.2024.040004
低开销的匿名通信群组威胁人物挖掘方法
A low-cost method for mining threat actor in anonymous communication groups
摘要
Abstract
The deep and dark web,due to its high anonymity,easy accessibility,and convenient transac-tions,has fostered a large number of illegal activities,including promoting online gambling and selling drugs.The development of online social interactions has led to the formation of groups on the encrypted instant mes-saging app Telegram,which act as gathering places for the promotion of cybercriminal activities and the ex-change of resources and tools.Many criminals are exploiting Telegram's anonymity feature to conduct busi-ness in groups with unrestricted content,short messages,and difficult-to-understand text,thereby evading regulation and posing a serious threat to national social stability and cybersecurity.Analyzing a substantial vol-ume of low-information content within groups has the potential to reveal numerous hidden threat actors,thereby providing regulatory,governance,and enforcement agencies with a wealth of valuable leads.This pa-per proposes a low-cost method for mining threat actors in anonymous communication groups,which adjusts the importance of network public hazard terminologies in the text to optimize the quality of content analysis.By the integration of large language models,this method conducts unsupervised and high-quality dynamic temporal topic extraction and visualized statistical analysis of group content.The experimental results demon-strate that the proposed method significantly reduces the cost of manual annotation,improves the quantity and quality of threat actor mining,and enhances understanding of the network public hazard ecosystem,and there-fore has practical implications when compared to traditional classification methods.关键词
网络公害/文本挖掘/Telegram群组/主题建模Key words
Network public hazard/Text mining/Telegram groups/Topic modeling分类
计算机与自动化引用本文复制引用
霍艺璇,赵佳鹏,时金桥,齐敏,孙岩炜,王学宾,杨燕燕..低开销的匿名通信群组威胁人物挖掘方法[J].四川大学学报（自然科学版）,2024,61(4):37-46,10.基金项目
国家重点研发计划"网络空间安全治理"专项(2023YFB3106600) （2023YFB3106600）
