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MixEth: Efficient, Trustless Coin Mixing Service for Ethereum

Authors István András Seres , Dániel A. Nagy, Chris Buckland, Péter Burcsi

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OASIcs.Tokenomics.2019.13.pdf
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Subject Classification

ACM Subject Classification
  • Theory of computation → Cryptographic protocols
Keywords
  • Cryptography
  • Verifiable shuffle
  • Anonymity
  • Cryptocurrency
  • Ethereum
  • Coin mixer
  • State Channel

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Abstract

Coin mixing is a prevalent privacy-enhancing technology for cryptocurrency users. In this paper, we present MixEth, which is a trustless coin mixing service for Turing-complete blockchains. MixEth does not rely on a trusted setup and is more efficient than any proposed trustless coin tumbler. It requires only 3 on-chain transactions at most per user and 1 off-chain message. It achieves strong notions of anonymity and is able to resist denial-of-service attacks. Furthermore the underlying protocol can also be used to efficiently shuffle ballots, ciphertexts in a trustless and decentralized manner.

Cite As Get BibTex

István András Seres, Dániel A. Nagy, Chris Buckland, and Péter Burcsi. MixEth: Efficient, Trustless Coin Mixing Service for Ethereum. In International Conference on Blockchain Economics, Security and Protocols (Tokenomics 2019). Open Access Series in Informatics (OASIcs), Volume 71, pp. 13:1-13:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/OASIcs.Tokenomics.2019.13

Author Details

István András Seres
  • Eötvös Loránd University, Hungary
Dániel A. Nagy
  • Eötvös Loránd University, Hungary
Chris Buckland
  • King’s College London, United Kingdom
Péter Burcsi
  • Eötvös Loránd University, Hungary

Funding

The research at Eötvös Loránd University was partially supported by the European Union, co-financed by the European Social Fund (EFOP-3.6.2-16-2017-00012).
  • Buckland, Chris: is supported by an Ethereum Foundation scaling grant and an Ethereum Community Fund grant.

Acknowledgements

We would like to thank Liam Horne for helping with the state channel implementation, Barry Whitehat, Dmitry Khovratovich and Sina Mahmoodi for the insightful comments and discussions.

Supplementary Materials

References

  1. barryWhiteHat. Miximus. https://github.com/barryWhiteHat/miximus, 2018.
  2. barryWhiteHat. Miximus gas costs. https://www.reddit.com/r/ethereum/comments/8ss53z/miximus_zksnark_based_anonymous_transactions_is/, 2018.
  3. Stephanie Bayer and Jens Groth. Efficient zero-knowledge argument for correctness of a shuffle. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 263-280. Springer, 2012. Google Scholar
  4. George Bissias, A Pinar Ozisik, Brian N Levine, and Marc Liberatore. Sybil-resistant mixing for bitcoin. In Proceedings of the 13th Workshop on Privacy in the Electronic Society, pages 149-158. ACM, 2014. Google Scholar
  5. Dan Boneh. The decision diffie-hellman problem. In International Algorithmic Number Theory Symposium, pages 48-63. Springer, 1998. Google Scholar
  6. Joseph Bonneau, Arvind Narayanan, Andrew Miller, Jeremy Clark, Joshua A Kroll, and Edward W Felten. Mixcoin: Anonymity for Bitcoin with accountable mixes. In International Conference on Financial Cryptography and Data Security, pages 486-504. Springer, 2014. Google Scholar
  7. Vitalik Buterin and Nick Johnson. EIP86: Account Abstraction. https://github.com/ethereum/EIPs/blob/master/EIPS/eip-86.md, 2017.
  8. Wren Chan and Aspen Olmsted. Ethereum transaction graph analysis. In 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST), pages 498-500. IEEE, 2017. Google Scholar
  9. David Chaum and Torben Pryds Pedersen. Wallet databases with observers. In Annual International Cryptology Conference, pages 89-105. Springer, 1992. Google Scholar
  10. Jeff Coleman, Liam Horne, and Li Xuanji. Counterfactual: Generalized state channels, 2018. Google Scholar
  11. Stefan Dziembowski, Lisa Eckey, Sebastian Faust, and Daniel Malinowski. Perun: Virtual payment channels over cryptographic currencies. Technical report, IACR Cryptology ePrint Archive, 2017: 635, 2017. Google Scholar
  12. Manuel Fersch, Eike Kiltz, and Bertram Poettering. On the provable security of (EC) DSA signatures. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pages 1651-1662. ACM, 2016. Google Scholar
  13. Ethan Heilman, Leen Alshenibr, Foteini Baldimtsi, Alessandra Scafuro, and Sharon Goldberg. TumbleBit: An untrusted Bitcoin-compatible anonymous payment hub. In Network and Distributed System Security Symposium, 2017. Google Scholar
  14. Greg Maxwell. CoinJoin: Bitcoin privacy for the real world. In Post on Bitcoin forum, 2013. Google Scholar
  15. Patrick McCorry, Chris Buckland, Surya Bakshi, Karl Wüst, and Andrew Miller. You sank my battleship! A case study to evaluate state channels as a scaling solution for cryptocurrencies. Google Scholar
  16. Sarah Meiklejohn and Rebekah Mercer. Möbius: Trustless tumbling for transaction privacy. Proceedings on Privacy Enhancing Technologies, 2018(2):105-121, 2018. Google Scholar
  17. Sarah Meiklejohn, Marjori Pomarole, Grant Jordan, Kirill Levchenko, Damon McCoy, Geoffrey M Voelker, and Stefan Savage. A fistful of bitcoins: characterizing payments among men with no names. In Proceedings of the 2013 conference on Internet measurement conference, pages 127-140. ACM, 2013. Google Scholar
  18. Pedro Moreno-Sanchez, Muhammad Bilal Zafar, and Aniket Kate. Listening to whispers of ripple: Linking wallets and deanonymizing transactions in the ripple network. Proceedings on Privacy Enhancing Technologies, 2016(4):436-453, 2016. Google Scholar
  19. Malte Moser, Rainer Bohme, and Dominic Breuker. An inquiry into money laundering tools in the Bitcoin ecosystem. In eCrime Researchers Summit (eCRS), 2013, pages 1-14. IEEE, 2013. Google Scholar
  20. Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system, 2008. Google Scholar
  21. Nchinda Nchinda. Exploring Pseudonimity on Ethereum. https://media.consensys.net/exploring-pseudonimity-on-ethereum-dda257019eb4, 2016.
  22. Serge Nedashkovsky. Huge Ethereum Mixer. https://blog.cyber.fund/huge-ethereum-mixer-6cf98680ee6c, 2017.
  23. C Andrew Neff. A verifiable secret shuffle and its application to e-voting. In Proceedings of the 8th ACM conference on Computer and Communications Security, pages 116-125. ACM, 2001. Google Scholar
  24. Joseph Poon and Thaddeus Dryja. The bitcoin lightning network: Scalable off-chain instant payments. https://lightning.network/lightning-network-paper.pdf, 2016.
  25. Tim Ruffing, Pedro Moreno-Sanchez, and Aniket Kate. CoinShuffle: Practical decentralized coin mixing for Bitcoin. In European Symposium on Research in Computer Security, pages 345-364. Springer, 2014. Google Scholar
  26. Luke Valenta and Brendan Rowan. Blindcoin: Blinded, accountable mixes for bitcoin. In International Conference on Financial Cryptography and Data Security, pages 112-126. Springer, 2015. Google Scholar
  27. Gavin Wood. Ethereum: A secure decentralised generalised transaction ledger. Ethereum project yellow paper, 151:1-32, 2014. Google Scholar
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