A game‐theoretic approach of mixing different qualities of coins

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.

[1]  Klaus Wehrle,et al.  CoinParty: Secure Multi-Party Mixing of Bitcoins , 2015, CODASPY.

[2]  Rainer Böhme,et al.  Towards Risk Scoring of Bitcoin Transactions , 2014, Financial Cryptography Workshops.

[3]  Julio Hernandez-Castro,et al.  An Analysis of Bitcoin Laundry Services , 2017, NordSec.

[4]  Hong Liu,et al.  A scalable coevolutionary multi-objective particle swarm optimizer , 2010, Int. J. Comput. Intell. Syst..

[5]  Chris Buckland,et al.  MixEth: efficient, trustless coin mixing service for Ethereum , 2019, IACR Cryptol. ePrint Arch..

[6]  Fengyin Li,et al.  A game-theoretic method based on Q-learning to invalidate criminal smart contracts , 2019, Inf. Sci..

[7]  Malte Möser,et al.  Effective Cryptocurrency Regulation Through Blacklisting , 2019 .

[8]  Xingtong Liu,et al.  Unlinkable Coin Mixing Scheme for Transaction Privacy Enhancement of Bitcoin , 2018, IEEE Access.

[9]  Hong Wang,et al.  Effective algorithms for vertical mining probabilistic frequent patterns in uncertain mobile environments , 2016, Int. J. Ad Hoc Ubiquitous Comput..

[10]  Malte Möser,et al.  An inquiry into money laundering tools in the Bitcoin ecosystem , 2013, 2013 APWG eCrime Researchers Summit.

[11]  Jiguo Yu,et al.  Research on direct anonymous attestation mechanism in enterprise information management , 2019, Enterp. Inf. Syst..

[12]  Xinchun Cui,et al.  Secure computation protocols under asymmetric scenarios in enterprise information system , 2019, Enterp. Inf. Syst..

[13]  A Goriacheva,et al.  Anonymization Technologies of Cryptocurrency Transactions as Money Laundering Instrument , 2018 .

[14]  Adi Shamir,et al.  Quantitative Analysis of the Full Bitcoin Transaction Graph , 2013, Financial Cryptography.

[15]  Tao Li,et al.  Randomness invalidates criminal smart contracts , 2019, Inf. Sci..

[16]  Jeremy Clark,et al.  SoK: Research Perspectives and Challenges for Bitcoin and Cryptocurrencies , 2015, 2015 IEEE Symposium on Security and Privacy.

[17]  T. Moore,et al.  Bitcoin: Economics, Technology, and Governance , 2014 .

[18]  Stefan Savage,et al.  A fistful of bitcoins: characterizing payments among men with no names , 2013, Internet Measurement Conference.

[19]  Antonio Pescapè,et al.  Internet Censorship detection: A survey , 2015, Comput. Networks.

[20]  Sarah Meiklejohn,et al.  Privacy-Enhancing Overlays in Bitcoin , 2015, Financial Cryptography Workshops.

[21]  Hong Wang,et al.  An attention mechanism and multi-granularity-based Bi-LSTM model for Chinese Q&A system , 2020, Soft Comput..

[22]  Dimitris Gritzalis,et al.  Browser Blacklists: The Utopia of Phishing Protection , 2014, ICETE.

[23]  Svetlana Abramova,et al.  Mixing Coins of Different Quality: A Game-Theoretic Approach , 2017, Financial Cryptography Workshops.

[24]  Tyler Moore,et al.  Measuring the Impact of Sharing Abuse Data with Web Hosting Providers , 2016, WISCS@CCS.

[25]  Xiangwei Zheng,et al.  A Multidomain Survivable Virtual Network Mapping Algorithm , 2017, Secur. Commun. Networks.

[26]  Ghassan O. Karame,et al.  Evaluating User Privacy in Bitcoin , 2013, Financial Cryptography.

[27]  S A R A H M E I K L E J O H N,et al.  A Fistful of Bitcoins Characterizing Payments Among Men with No Names , 2013 .

[28]  PescapéAntonio,et al.  Internet Censorship detection , 2015 .

[29]  Fergal Reid,et al.  An Analysis of Anonymity in the Bitcoin System , 2011, PASSAT 2011.