Research on Intelligence Mining of Illegal Underground Internet Production on Anonymous Network : Taking Personal Information Trading as an Example

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC) Pub Date : 2023-02-24 DOI:10.1109/ITNEC56291.2023.10081964

Guangxuan Chen, Guangxiao Chen, Di Wu, Qiang Liu, Lei Zhang

{"title":"Research on Intelligence Mining of Illegal Underground Internet Production on Anonymous Network : Taking Personal Information Trading as an Example","authors":"Guangxuan Chen, Guangxiao Chen, Di Wu, Qiang Liu, Lei Zhang","doi":"10.1109/ITNEC56291.2023.10081964","DOIUrl":null,"url":null,"abstract":"As law enforcement agencies continue to strengthen their efforts to crack down on illegal underground Internet production trading activities, criminals gradually transfer illegal personal information trading and other illegal products, as well as other related crimes, to anonymous networks. Taking Tor dark network as the target, this paper designs active node detection methods and passive node detection methods to obtain criminal intelligence on the dark network. Through the design of the dark web crawler, a large number of personal information transaction related data were obtained. At the same time, the data were analyzed in time, space, type and theme dimensions, forming effective and targeted information. The intelligence mining method proposed in this paper can effectively collect the data related to the subject, form the multi-dimensional analysis results that can be displayed according to the needs, and provide certain technical support for the law enforcement agencies to fight against the hidden network crime.","PeriodicalId":218770,"journal":{"name":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNEC56291.2023.10081964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

Abstract

As law enforcement agencies continue to strengthen their efforts to crack down on illegal underground Internet production trading activities, criminals gradually transfer illegal personal information trading and other illegal products, as well as other related crimes, to anonymous networks. Taking Tor dark network as the target, this paper designs active node detection methods and passive node detection methods to obtain criminal intelligence on the dark network. Through the design of the dark web crawler, a large number of personal information transaction related data were obtained. At the same time, the data were analyzed in time, space, type and theme dimensions, forming effective and targeted information. The intelligence mining method proposed in this paper can effectively collect the data related to the subject, form the multi-dimensional analysis results that can be displayed according to the needs, and provide certain technical support for the law enforcement agencies to fight against the hidden network crime.

查看原文本刊更多论文

匿名网络下非法地下互联网生产的智能挖掘研究——以个人信息交易为例

随着执法部门对非法网络地下生产交易活动的打击力度不断加大，犯罪分子逐渐将非法个人信息交易等非法产品以及其他相关犯罪转移到匿名网络上。本文以Tor暗网络为目标，设计了主动节点检测方法和被动节点检测方法来获取暗网络上的犯罪情报。通过暗网爬虫的设计，获得了大量个人信息交易的相关数据。同时，从时间、空间、类型、主题等维度对数据进行分析，形成有效、有针对性的信息。本文提出的情报挖掘方法可以有效地收集与主题相关的数据，形成可根据需要显示的多维度分析结果，为执法机关打击隐性网络犯罪提供一定的技术支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)

自引率

0.00%

发文量