面向加密货币反洗钱的智能监管研究：模型、方法与应用

张昳斐; 袁勇; 杨东; 王飞跃

doi:10.11959/j.issn.2096-6652.202522

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面向加密货币反洗钱的智能监管研究：模型、方法与应用

综述与展望 | 更新时间：2025-07-21

- 面向加密货币反洗钱的智能监管研究：模型、方法与应用
- Intelligent regulation for cryptocurrency anti-money laundering: models, methods, and applications
- 智能科学与技术学报 2025年7卷第2期页码：165-183
- 作者机构：
  
  1.中国人民大学数学学院，北京 100872
  2.中国人民大学法学院，北京 100872
  3.中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
- 作者简介：
  
  [ "张昳斐（1997- ），女，中国人民大学数学学院硕士生，主要研究方向为区块链与加密货币监管。" ]
  [ "袁勇（1980- ），男，博士，中国人民大学数学学院教授，主要研究方向为区块链、计算经济学和分布式人工智能。" ]
  [ "杨东（1975- ），男，博士，中国人民大学法学院教授，主要研究方向为金融科技、区块链、数字货币。" ]
  [ "王飞跃（1961- ），男，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任，澳门科技大学特聘教授，主要研究方向为平行系统的方法与应用、社会计算、平行智能、知识自动化。" ]
- 基金信息：
  
  国家重点研发计划项目(2022YFB2720401);国家自然科学基金项目(72171230);北京市未来区块链与隐私计算高精尖中心项目
- DOI：10.11959/j.issn.2096-6652.202522
  中图分类号： F831
- 收稿：2025-03-04，
  
  修回：2025-05-06，
  
  纸质出版：2025-06-15
- 稿件说明：
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张昳斐,袁勇,杨东等.面向加密货币反洗钱的智能监管研究：模型、方法与应用[J].智能科学与技术学报,2025,07(02):165-183.

ZHANG Yifei,YUAN Yong,YANG Dong,et al.Intelligent regulation for cryptocurrency anti-money laundering: models, methods, and applications[J].Chinese Journal of Intelligent Science and Technology,2025,07(02):165-183.
张昳斐,袁勇,杨东等.面向加密货币反洗钱的智能监管研究：模型、方法与应用[J].智能科学与技术学报,2025,07(02):165-183. DOI： 10.11959/j.issn.2096-6652.202522.

ZHANG Yifei,YUAN Yong,YANG Dong,et al.Intelligent regulation for cryptocurrency anti-money laundering: models, methods, and applications[J].Chinese Journal of Intelligent Science and Technology,2025,07(02):165-183. DOI： 10.11959/j.issn.2096-6652.202522.

摘要

近年来，基于区块链技术的加密货币市场正在快速发展，新兴商业模式和应用场景不断涌现，形成了数万亿美元规模的新经济体系。加密货币具有去中心化、匿名性和易于跨境流通等特性，极大地丰富和发展了以法定货币为核心的主流金融体系，同时也被广泛应用于洗钱等非法金融活动。因此，面向加密货币反洗钱的监管研究成为新兴热点领域，而机器学习和人工智能则成为加密货币交易行为监管、交易网络分析、安全风险评估等领域的主要研究方法。首先，系统性地梳理了近年来加密货币反洗钱的智能监管研究进展，从传统机器学习、深度学习、集成学习、图分析和启发式方法等维度归纳总结了反洗钱监管研究的主要模型、方法和应用模式。同时，整理了加密货币反洗钱研究文献中的常用数据集，并基于Elliptic数据集给出现有模型和算法的性能对比。最后，讨论了加密货币反洗钱的研究挑战与未来发展方向，以期为加密货币和去中心化金融产业的繁荣与健康发展提供有益的参考和借鉴。

Abstract

In recent years

blockchain-enabled cryptocurrency market has been rapidly evolving to a trillion-dollar economic system with various kinds of emerging business models and application scenarios. Cryptocurrencies

characterized by decentralization

anonymity

and ease of cross-border circulation

have significantly enriched and evolved the mainstream financial system centered around fiat currencies. However

they are also extensively used in illegal financial activities including money laundering. As such

research on anti-money laundering (AML) regulation for cryptocurrencies has become a burgeoning field of interest

with machine learning and artificial intelligence (AI) emerging as primary methodologies in areas such as cryptocurrency transaction monitoring

transaction network analysis

and security risk assessment. First

the recent research progress on intelligent AML regulation for cryptocurrencies was systematically reviewed. The main models

methods

and application patterns in AML regulatory research were summarized from multiple dimensions

including traditional machine learning

deep learning

ensemble learning

graph analysis

and heuristic approaches. Meanwhile

commonly used datasets in cryptocurrency AML research were compiled

and a performance comparison of existing models and algorithms was provided based on the Elliptic dataset. Finally

the research challenges and future directions of cryptocurrency AML were discussed

aiming to offer valuable references and insights for the prosperity and healthy development of the cryptocurrency and decentralized finance industry.

关键词

Keywords

references

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