数字货币交易匿名性与监管的博弈分析

张娴; 朱建明; 隋智源; 明盛智

doi:10.11959/j.issn.2096-109x.2022068

您当前的位置：

首页 >

文章列表页 >

数字货币交易匿名性与监管的博弈分析

学术论文 | 更新时间：2024-06-03

- 数字货币交易匿名性与监管的博弈分析
- Analysis on anonymity and regulation of digital currency transactions based on game theory
- 网络与信息安全学报 2022年8卷第5期页码：150-157
- 作者机构：
- 作者简介：
  
  [ "张娴（1998- ），女，河南开封人，中央财经大学硕士生，主要研究方向为区块链安全、隐私保护、数字货币" ]
  [ "朱建明（1965- ），男，山西太原人，中央财经大学教授、博士生导师，主要研究方向为信息安全、区块链技术、隐私保护" ]
  [ "隋智源（1984- ），男，山东诸城人，中央财经大学讲师，主要研究方向为应用密码学、信息安全、隐私保护" ]
  [ "明盛智（1999- ），男，广西桂林人，中央财经大学硕士生，主要研究方向为区块链技术、隐私保护、隐私计算" ]
- 基金信息：
  
  中央财经大学新兴交叉学科建设项目;Emerging Interdisciplinary Project of CUFE
- DOI：10.11959/j.issn.2096-109x.2022068
  中图分类号： TP393
- 网络首发：2022-10，
  
  纸质出版：2022-10-15
- 稿件说明：
移动端阅览
张娴, 朱建明, 隋智源, 等. 数字货币交易匿名性与监管的博弈分析[J]. 网络与信息安全学报, 2022,8(5):150-157.

Xian ZHANG, Jianming ZHU, Zhiyuan SUI, et al. Analysis on anonymity and regulation of digital currency transactions based on game theory[J]. Chinese Journal of Network and Information Security, 2022, 8(5): 150-157.
张娴, 朱建明, 隋智源, 等. 数字货币交易匿名性与监管的博弈分析[J]. 网络与信息安全学报, 2022,8(5):150-157. DOI： 10.11959/j.issn.2096-109x.2022068.

Xian ZHANG, Jianming ZHU, Zhiyuan SUI, et al. Analysis on anonymity and regulation of digital currency transactions based on game theory[J]. Chinese Journal of Network and Information Security, 2022, 8(5): 150-157. DOI： 10.11959/j.issn.2096-109x.2022068.

摘要

通过利用区块链等技术，数字货币作为一种新型货币资产推动了数字经济的发展。数字货币交易平台在数字货币用户对私有数字货币使用中占有重要角色。现有的数字货币交易平台可能存在泄露用户个人隐私的风险，为不法分子提供参与“空投”事件、勒索、骗局等各种异常交易行为的条件；数字货币交易平台对用户强匿名性保护也会增加监管部门对于数字货币交易情况的监管难度。因此数字货币交易平台选择对用户的匿名性保护的强弱不仅需要考虑用户的个人隐私安全，而且要考虑如何符合监管部门对其监管工作的要求。基于对数字货币交易平台和监管部门之间关系的分析，建立演化博弈模型，对数字货币交易平台与监管博弈模型进行定义和构建，根据数字货币交易平台与监管部门收益矩阵求解复制动态方程并得出均衡解。通过构建雅可比矩阵对演化系统在不同参数取值下的均衡点进行稳定性分析，并分析在不同情况下，数字货币交易平台与监管部门的演化稳定选择及策略。结合Matlab实验环境，对数字货币交易平台的强弱匿名性保护策略和监管部门的强弱监管策略进行仿真实验，验证博弈模型的准确性。结合实验结果，提出对数字货币交易平台的监管建议，为我国将来开展数字货币交易平台的监管工作提供理论依据。

Abstract

By using technologies such as blockchain

digital currency

as a new type of monetary asset

has been promoting the development of digital economy.Digital currency trading platform plays an important role in the use of private digital currency by digital currency users.Existing digital currency trading platforms may expose users’ privacy and provide illegal elements with the conditions to participate in various abnormal trading behaviors such as“air dropping” events

extortion

fraud

etc.The strong anonymity protection of users by digital currency trading platforms also make it more difficult for regulatory authorities to supervise digital currency transactions.Therefore

the strength of the anonymity protection of users by digital currency trading platforms need to consider not only the privacy protection of users

but also meet the regulatory requirements.For this reason

based on the analysis of the relationship between the digital currency trading platforms and the supervisory departments

an evolutionary game model was established

the digital currency trading platform and the supervisory game model were defined and constructed

and the replication dynamic equation was solved and the balanced solution was obtained according to the income matrix between the digital currency trading platform and the supervisory department.By building a Jacobian matrix

the stability of the evolutionary system under different parameters was analyzed.Besides

the evolutionary stable selection and strategy of the digital currency trading platform and the regulatory authority under different conditions were also analyzed.With Matlab

different strategies of anonymity protection of the digital currency trading platform and different strategies of supervision strategy of the regulatory department were simulated to verify the accuracy of the game model.Based on the results of the simulations

some suggestions on the supervision of digital currency trading platforms are put forward

which provides a theoretical basis for the future supervision of digital currency trading platforms in China.

关键词

Keywords

references

付烁 , 徐海霞 , 李佩丽 , 等 . 数字货币的匿名性研究 [J ] . 计算机学报 , 2018 , 42 ( 5 ): 1045 - 1062 .

FU S , XU H X , LI P L , et al . A survey on anonymity of digital currency [J ] . Chinese Journal of Computers , 2018 , 42 ( 5 ): 1045 - 1062 .

曾宪力 . 私人数字货币的法律属性及监管研究 [D ] . 上海:华东政法大学 , 2021 .

ZENG X L . Research on legal attribute and supervision of private digital currency [D ] . Shanghai:East China University of Political Science and Law , 2021 .

沈蒙 , 桑安琪 , 祝烈煌 , 等 . 基于动机分析的区块链数字货币异常交易行为识别方法 [J ] . 计算机学报 , 2021 , 44 ( 1 ): 193 - 208 .

SHEN M , SANG A Q , ZHU L H , et al . Abnormal transaction behavior recognition based on motivation analysis in blockchain digital currency [J ] . Chinese Journal of Computers , 2021 , 44 ( 1 ): 193 - 208 .

胡俏 , 齐佳音 . 基于SD演化博弈模型的数字货币扩散演化仿真研究 [J ] . 系统工程理论与实践 , 2021 , 41 ( 5 ): 1211 - 1228 .

HU Q , QI J Y . Cryptocurrency diffusion evolution simulation based on SD evolution game model [J ] . Systems Engineering-Theory ＆Practice , 2021 , 41 ( 5 ): 1211 - 1228 .

郭阳楠 , 蒋文保 , 叶帅 . 可监管的区块链匿名交易系统模型 [J ] . 计算机应用 , 2022 , 42 ( 9 ): 2757 - 2764 .

GUO Y N , JIANG W B , YE S . Supervisable blockchain anonymous transaction system model [J ] . Journal of Computer Applications , 2022 , 42 ( 9 ): 2757 - 2764 .

张前程 , 王明成 . 农村金融监管的演化博弈模型分析 [J ] . 安徽工业大学学报(社会科学版) , 2010 , 27 ( 5 ): 3 - 5 .

ZHANG Q C , WANG M C . Evolutionary game analysis of rural financial supervision [J ] . Journal of Anhui University of Technology (Social Sciences) , 2010 , 27 ( 5 ): 3 - 5 .

刘荣 , 王凤兰 , 王非 . 基于演化博弈模型的网络攻防策略 [J ] . 科学技术与工程 , 2020 , 20 ( 21 ): 8671 - 8675 .

LIU R , WANG F L , WANG F . Network attack and defense strategy based on evolutionary game model [J ] . Science Technology and Engineering , 2020 , 20 ( 21 ): 8671 - 8675 .

丁佳 . 第三方支付机构洗钱风险的评估与监管问题研究 [D ] . 南京:南京师范大学 , 2019 .

DING J . Third-party payment institution money laundering risk assessment and regulatory issues research [D ] . Nanjing:Nanjing Normal University , 2019 .

浏览量

417

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于隐私集合求交的大模型双向隐私授权

基于PIR增强的可搜索加密方案研究

面向LBS的ADS-B报文定位数据本地化差分隐私保护方法

FL-IoV：基于联邦学习的综合车联网入侵检测方法

面向异构数据的半分布式联邦学习安全聚合