摘要
[目的/意义]加密数字货币交易呈现出匿名性、全球性、成本低等特点,非常契合恐怖分子和犯罪团伙在全球范围内转移资金的需求。对加密数字货币交易进行有效监管已成为学术界、工业界和相关执法部门重点关注的问题。[研究设计/方法]依托以比特币为代表的加密数字货币交易数据,利用社会网络分析方法识别异常地址和交易模式,并使用机器学习算法判断比特币拥有者的实体身份。[结论/发现]通过对真实发生的比特币恐怖融资案例进行交易追踪与溯源,验证本文提出的方法可以有效地识别加密数字货币交易中的恐怖融资实体,发现典型的恐怖组织资金转移交易模式。[创新/价值]通过对交易数据的挖掘分析研究数字货币的黑暗面,对数字货币和区块链的监管具有一定的现实意义和理论价值。
[Purpose/Significance]Cryptocurrency transaction is globally anonymous with low cost,which is in favor of terrorists and criminals to transfer funds around the world.Effective supervision of cryptocurrency transactions has become a challenge for academia,industry and relevant law enforcement agencies.[Design/Methodology]Relying on transaction data of Bitcoin as a representative cryptocurrency,this study conducts social network analysis to identify abnormal addresses and transaction patterns,and utilizes machine learning algorithms to identify Bitcoin owners.[Findings/Conclusion]Through the analysis of real cases of Bitcoin terrorist financing,it is proved that our proposed method is effective in identifying terrorist financing entities and detecting typical fund transaction patterns of terrorist organizations in cryptocurrency transactions.[Originality/Value]This paper studies the dark side of cryptocurrency transactions through data mining and analysis,which has both practical significance and theoretical value for the regulation of cryptocurrencies and blockchain.
作者
颜嘉麒
王佳鑫
毛谦昂
严丹妮
YAN Jiaqi;WANG Jiaxin;MAO Qianang;YAN Danni
出处
《图书情报知识》
CSSCI
北大核心
2022年第6期55-66,共12页
Documentation,Information & Knowledge
基金
国家自然科学基金项目“恐怖主义数字货币融资交易实体角色识别与知识图谱分析方法研究”(72171115)的研究成果之一。
关键词
比特币
恐怖融资
区块链
网络分析
机器学习
Bitcoin
Terrorist financing
Blockchain
Network analysis
Machine learning
