Document Open Access Logo

The Power of Random Symmetry-Breaking in Nakamoto Consensus

Authors Lili Su, Quanquan C. Liu, Neha Narula

PDF

File

Thumbnail PDF
PDF
LIPIcs.DISC.2021.39.pdf
  • Filesize: 0.73 MB
  • 19 pages

Document Identifiers

Related Versions

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed computing models
Keywords
  • Nakamoto consensus
  • Byzantine consensus
  • blockchain
  • symmetry-breaking
  • coalescing random walks

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

Abstract

Nakamoto consensus underlies the security of many of the world’s largest cryptocurrencies, such as Bitcoin and Ethereum. Common lore is that Nakamoto consensus only achieves consistency and liveness under a regime where the difficulty of its underlying mining puzzle is very high, negatively impacting overall throughput and latency. In this work, we study Nakamoto consensus under a wide range of puzzle difficulties, including very easy puzzles. We first analyze an adversary-free setting and show that, surprisingly, the common prefix of the blockchain grows quickly even with easy puzzles. In a setting with adversaries, we provide a small backwards-compatible change to Nakamoto consensus to achieve consistency and liveness with easy puzzles. Our insight relies on a careful choice of symmetry-breaking strategy, which was significantly underestimated in prior work. We introduce a new method - coalescing random walks - to analyzing the correctness of Nakamoto consensus under the uniformly-at-random symmetry-breaking strategy. This method is more powerful than existing analysis methods that focus on bounding the number of convergence opportunities.

Cite As Get BibTex

Lili Su, Quanquan C. Liu, and Neha Narula. The Power of Random Symmetry-Breaking in Nakamoto Consensus. In 35th International Symposium on Distributed Computing (DISC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 209, pp. 39:1-39:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.DISC.2021.39

Author Details

Lili Su
  • Northeastern University, Boston, MA, USA
Quanquan C. Liu
  • Massachusetts Institute of Technology, Cambridge, MA, USA
Neha Narula
  • Massachusetts Institute of Technology, Cambridge, MA, USA

References

  1. David Aldous and Jim Fill. Reversible markov chains and random walks on graphs, 2002. Google Scholar
  2. Vivek Bagaria, Sreeram Kannan, David Tse, Giulia Fanti, and Pramod Viswanath. Prism: Deconstructing the blockchain to approach physical limits. In Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, pages 585-602, 2019. Google Scholar
  3. Erica Blum, Aggelos Kiayias, Cristopher Moore, Saad Quader, and Alexander Russell. The Combinatorics of the Longest-Chain Rule: Linear Consistency for Proof-of-Stake Blockchains, pages 1135-1154. SIAM, 2020. URL: https://doi.org/10.1137/1.9781611975994.69.
  4. Dan Boneh, Joseph Bonneau, Benedikt Bünz, and Ben Fisch. Verifiable delay functions. In Advances in Cryptology - CRYPTO 2018 - 38th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 19-23, 2018, Proceedings, Part I, pages 757-788, 2018. URL: https://doi.org/10.1007/978-3-319-96884-1_25.
  5. Dan Boneh, Joseph Bonneau, Benedikt Bünz, and Ben Fisch. Verifiable delay functions. Cryptology ePrint Archive, Report 2018/601, 2018. URL: https://eprint.iacr.org/2018/601.
  6. Colin Cooper, Robert Elsasser, Hirotaka Ono, and Tomasz Radzik. Coalescing random walks and voting on connected graphs. SIAM Journal on Discrete Mathematics, 27(4):1748-1758, 2013. Google Scholar
  7. Colin Cooper, Alan Frieze, and Tomasz Radzik. Multiple random walks in random regular graphs. SIAM Journal on Discrete Mathematics, 23(4):1738-1761, 2010. Google Scholar
  8. Matt Corallo. Compact block relay, 2016. URL: https://github.com/bitcoin/bips/blob/master/bip-0152.mediawiki.
  9. Cynthia Dwork and Moni Naor. Pricing via processing or combatting junk mail. In Annual international cryptology conference, pages 139-147. Springer, 1992. Google Scholar
  10. EOS. v2.0 consensus protocol, 2021. URL: https://developers.eos.io/welcome/v2.0/protocol/consensus_protocol.
  11. Ittay Eyal and Emin Gün Sirer. Majority is not enough: Bitcoin mining is vulnerable. In International conference on financial cryptography and data security, pages 436-454. Springer, 2014. Google Scholar
  12. Juan Garay, Aggelos Kiayias, and Nikos Leonardos. The bitcoin backbone protocol: Analysis and applications. In Elisabeth Oswald and Marc Fischlin, editors, Advances in Cryptology - EUROCRYPT 2015, pages 281-310, Berlin, Heidelberg, 2015. Springer Berlin Heidelberg. Google Scholar
  13. Juan Garay, Aggelos Kiayias, and Nikos Leonardos. The bitcoin backbone protocol: Analysis and applications. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 281-310. Springer, 2015. Google Scholar
  14. Juan Garay, Aggelos Kiayias, and Nikos Leonardos. Full analysis of nakamoto consensus in bounded-delay networks. Cryptology ePrint Archive, Report 2020/277, 2020. URL: https://eprint.iacr.org/2020/277.
  15. Juan A. Garay, Aggelos Kiayias, and Nikos Leonardos. The bitcoin backbone protocol with chains of variable difficulty. In Jonathan Katz and Hovav Shacham, editors, Advances in Cryptology - CRYPTO 2017 - 37th Annual International Cryptology Conference, Santa Barbara, CA, USA, August 20-24, 2017, Proceedings, Part I, volume 10401 of Lecture Notes in Computer Science, pages 291-323. Springer, 2017. URL: https://doi.org/10.1007/978-3-319-63688-7_10.
  16. Aggelos Kiayias and Giorgos Panagiotakos. Speed-security tradeoffs in blockchain protocols. IACR Cryptol. ePrint Arch., 2015:1019, 2015. URL: http://eprint.iacr.org/2015/1019.
  17. Lucianna Kiffer, Rajmohan Rajaraman, and abhi shelat. A better method to analyze blockchain consistency. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, CCS '18, page 729–744, New York, NY, USA, 2018. Association for Computing Machinery. URL: https://doi.org/10.1145/3243734.3243814.
  18. Silvio Micali. Algorand 2021 performance, 2020. URL: https://www.algorand.com/resources/blog/algorand-2021-performance.
  19. Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system, 2009. URL: http://www.bitcoin.org/bitcoin.pdf.
  20. Satoshi Nakamoto et al. Bitcoin: A peer-to-peer electronic cash system.(2008), 2008. Google Scholar
  21. Rafael Pass, Lior Seeman, and Abhi Shelat. Analysis of the blockchain protocol in asynchronous networks. In Jean-Sébastien Coron and Jesper Buus Nielsen, editors, Advances in Cryptology - EUROCRYPT 2017, pages 643-673, Cham, 2017. Springer International Publishing. Google Scholar
  22. Rafael Pass, Lior Seeman, and Abhi Shelat. Analysis of the blockchain protocol in asynchronous networks. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 643-673. Springer, 2017. Google Scholar
  23. Rafael Pass and Elaine Shi. Fruitchains: A fair blockchain. In Proceedings of the ACM Symposium on Principles of Distributed Computing, PODC '17, page 315–324, New York, NY, USA, 2017. Association for Computing Machinery. URL: https://doi.org/10.1145/3087801.3087809.
  24. Ling Ren. Analysis of nakamoto consensus. IACR Cryptol. ePrint Arch., 2019:943, 2019. URL: https://eprint.iacr.org/2019/943.
  25. Ayelet Sapirshtein, Yonatan Sompolinsky, and Aviv Zohar. Optimal selfish mining strategies in bitcoin. In International Conference on Financial Cryptography and Data Security, pages 515-532. Springer, 2016. Google Scholar
  26. R. Zhang and B. Preneel. Lay down the common metrics: Evaluating proof-of-work consensus protocols' security. In 2019 IEEE Symposium on Security and Privacy (SP), pages 175-192, 2019. URL: https://doi.org/10.1109/SP.2019.00086.
  27. Jun Zhao, Jing Tang, Zengxiang Li, Huaxiong Wang, Kwok-Yan Lam, and Kaiping Xue. An analysis of blockchain consistency in asynchronous networks: Deriving a neat bound. In 40th IEEE International Conference on Distributed Computing Systems, ICDCS 2020, Singapore, November 29 - December 1, 2020, pages 179-189. IEEE, 2020. URL: https://doi.org/10.1109/ICDCS47774.2020.00039.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact