A game‐theoretic approach of mixing different qualities of coins. Issue 12 (25th August 2020)

• Record Type: Journal Article
• Authors: Liu, Xiaozhang; Yu, Xinying; Zhu, Haojia; Yang, Guoyu; Wang, Yilei; Yu, Xiaomei
• Is Part Of: International journal of intelligent systems. Volume 35:Issue 12(2020)
• Page Start: 1899
• Page End: 1911
• Publication Date: 2020-08-25
• Subjects: anonymity -- Bitcoin -- game theory -- policy -- smart contract; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22277
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: Perpetrators leverage the untraceable feature to conduct illegal behaviors leading security issues with respect to mixing coins. Generally, bad coins are blocked based on a common blacklist. However, the blacklist may not be updated in time, which results in that bad coins escape the blocking. Consequently, perpetrators can still conduct illicit behaviors such as money laundering. In this paper, we apply game theory under imperfect information to study how coins' quality restrain these illicit behaviors under the incomplete scenario. More specifically, we propose a strategy for participants to submit deposits if they hope to mix coins with others even if they are not in blacklist at this time. The deposits will not be refunded when participants are included in the blacklist after mixing. Therefore, no participants have incentives to mix with bad coins. At the last part of this paper, we also simulate the incomes for participants, which indicates that deposits strategy is effective to prevent illicit behaviors.