When Is Spring Coming? A Security Analysis of Avalanche Consensus

Authors Ignacio Amores-Sesar , Christian Cachin , Enrico Tedeschi



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Author Details

Ignacio Amores-Sesar
  • University of Bern, Switzerland
Christian Cachin
  • University of Bern, Switzerland
Enrico Tedeschi
  • The Arctic University of Norway, Tromsø, Norway

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Ignacio Amores-Sesar, Christian Cachin, and Enrico Tedeschi. When Is Spring Coming? A Security Analysis of Avalanche Consensus. In 26th International Conference on Principles of Distributed Systems (OPODIS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 253, pp. 10:1-10:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.OPODIS.2022.10

Abstract

Avalanche is a blockchain consensus protocol with exceptionally low latency and high throughput. This has swiftly established the corresponding token as a top-tier cryptocurrency. Avalanche achieves such remarkable metrics by substituting proof of work with a random sampling mechanism. The protocol also differs from Bitcoin, Ethereum, and many others by forming a directed acyclic graph (DAG) instead of a chain. It does not totally order all transactions, establishes a partial order among them, and accepts transactions in the DAG that satisfy specific properties. Such parallelism is widely regarded as a technique that increases the efficiency of consensus. Despite its success, Avalanche consensus lacks a complete abstract specification and a matching formal analysis. To address this drawback, this work provides first a detailed formulation of Avalanche through pseudocode. This includes features that are omitted from the original whitepaper or are only vaguely explained in the documentation. Second, the paper gives an analysis of the formal properties fulfilled by Avalanche in the sense of a generic broadcast protocol that only orders related transactions. Last but not least, the analysis reveals a vulnerability that affects the liveness of the protocol. A possible solution that addresses the problem is also proposed.

Subject Classification

ACM Subject Classification
  • Theory of computation → Cryptographic protocols
  • Software and its engineering → Distributed systems organizing principles
Keywords
  • Avalanche
  • security analysis
  • generic broadcast

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References

  1. Ignacio Amores-Sesar, Christian Cachin, and Jovana Micic. Security analysis of ripple consensus. In OPODIS, volume 184 of LIPIcs, pages 10:1-10:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. Google Scholar
  2. Ignacio Amores-Sesar, Christian Cachin, and Enrico Tedeschi. When is spring coming? A security analysis of avalanche consensus. CoRR, abs/2210.03423, 2022. URL: http://arxiv.org/abs/2210.03423.
  3. Frederik Armknecht, Ghassan O. Karame, Avikarsha Mandal, Franck Youssef, and Erik Zenner. Ripple: Overview and outlook. In TRUST, volume 9229 of Lecture Notes in Computer Science, pages 163-180. Springer, 2015. Google Scholar
  4. Ava Labs, Inc. Avalanche documentation. URL: https://docs.avax.network/.
  5. Ava Labs, Inc. Node implementation for the Avalanche network. URL: https://github.com/ava-labs/avalanchego.
  6. Christian Cachin, Rachid Guerraoui, and Luís E. T. Rodrigues. Introduction to Reliable and Secure Distributed Programming (2. ed.). Springer, 2011. Google Scholar
  7. Christian Cachin, Klaus Kursawe, Frank Petzold, and Victor Shoup. Secure and efficient asynchronous broadcast protocols. In CRYPTO, volume 2139 of Lecture Notes in Computer Science, pages 524-541. Springer, 2001. Google Scholar
  8. Christian Cachin and Marko Vukolic. Blockchain consensus protocols in the wild (keynote talk). In DISC, volume 91 of LIPIcs, pages 1:1-1:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017. Google Scholar
  9. Coinmarketcap: Today’s cryptocurrency prices by market cap. https://coinmarketcap.com/, 2022.
  10. Bernardo David, Peter Gazi, Aggelos Kiayias, and Alexander Russell. Ouroboros praos: An adaptively-secure, semi-synchronous proof-of-stake blockchain. In EUROCRYPT (2), volume 10821 of Lecture Notes in Computer Science, pages 66-98. Springer, 2018. Google Scholar
  11. Cynthia Dwork, Nancy A. Lynch, and Larry J. Stockmeyer. Consensus in the presence of partial synchrony. J. ACM, 35(2):288-323, 1988. Google Scholar
  12. Ittay Eyal and Emin Gün Sirer. Majority is not enough: Bitcoin mining is vulnerable. In Financial Cryptography, volume 8437 of Lecture Notes in Computer Science, pages 436-454. Springer, 2014. Google Scholar
  13. Juan A. Garay, Aggelos Kiayias, and Nikos Leonardos. The bitcoin backbone protocol: Analysis and applications. In EUROCRYPT (2), volume 9057 of Lecture Notes in Computer Science, pages 281-310. Springer, 2015. Google Scholar
  14. Juan A. Garay, Aggelos Kiayias, and Nikos Leonardos. The bitcoin backbone protocol with chains of variable difficulty. In CRYPTO (1), volume 10401 of Lecture Notes in Computer Science, pages 291-323. Springer, 2017. Google Scholar
  15. Yossi Gilad, Rotem Hemo, Silvio Micali, Georgios Vlachos, and Nickolai Zeldovich. Algorand: Scaling byzantine agreements for cryptocurrencies. In SOSP, pages 51-68. ACM, 2017. Google Scholar
  16. Idit Keidar, Eleftherios Kokoris-Kogias, Oded Naor, and Alexander Spiegelman. All you need is DAG. In PODC, pages 165-175. ACM, 2021. Google Scholar
  17. Aggelos Kiayias, Alexander Russell, Bernardo David, and Roman Oliynykov. Ouroboros: A provably secure proof-of-stake blockchain protocol. In CRYPTO (1), volume 10401 of Lecture Notes in Computer Science, pages 357-388. Springer, 2017. Google Scholar
  18. Minjeong Kim, Yujin Kwon, and Yongdae Kim. Is stellar as secure as you think? In EuroS&P Workshops, pages 377-385. IEEE, 2019. Google Scholar
  19. Chenxing Li, Peilun Li, Wei Xu, Fan Long, and Andrew Chi-Chih Yao. Scaling nakamoto consensus to thousands of transactions per second. CoRR, abs/1805.03870, 2018. URL: http://arxiv.org/abs/1805.03870.
  20. Chenxing Li, Peilun Li, Dong Zhou, Zhe Yang, Ming Wu, Guang Yang, Wei Xu, Fan Long, and Andrew Chi-Chih Yao. A decentralized blockchain with high throughput and fast confirmation. In USENIX Annual Technical Conference, pages 515-528. USENIX Association, 2020. Google Scholar
  21. Marta Lokhava, Giuliano Losa, David Mazières, Graydon Hoare, Nicolas Barry, Eli Gafni, Jonathan Jove, Rafal Malinowsky, and Jed McCaleb. Fast and secure global payments with stellar. In SOSP, pages 80-96. ACM, 2019. Google Scholar
  22. Hamed Mamache, Gabin Mazué, Osama Rashid, Gewu Bu, and Maria Potop-Butucaru. Resilience of IOTA consensus. CoRR, abs/2111.07805, 2021. URL: http://arxiv.org/abs/2111.07805.
  23. Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system. Whitepaper, https://bitcoin.org/bitcoin.pdf, 2009.
  24. Marshall C. Pease, Robert E. Shostak, and Leslie Lamport. Reaching agreement in the presence of faults. J. ACM, 27(2):228-234, 1980. Google Scholar
  25. Fernando Pedone and André Schiper. Generic broadcast. In DISC, volume 1693 of Lecture Notes in Computer Science, pages 94-108. Springer, 1999. Google Scholar
  26. Sheldon Ross. Stochastic Processes. Wiley, second edition, 1996. Google Scholar
  27. Yonatan Sompolinsky, Shai Wyborski, and Aviv Zohar. PHANTOM GHOSTDAG: a scalable generalization of nakamoto consensus: September 2, 2021. In AFT, pages 57-70. ACM, 2021. Google Scholar
  28. W. Y. Tan. On the absorption probabilities and absorption times of finite homogeneous birth-death processes. Biometrics, 32(4):745-752, 1976. Google Scholar
  29. Team Rocket, Maofan Yin, Kevin Sekniqi, Robbert van Renesse, and Emin Gün Sirer. Scalable and probabilistic leaderless BFT consensus through metastability. e-print, arXiv:1906.08936 [cs.CR], 2019. Google Scholar
  30. Bozhi Wang, Qin Wang, Shiping Chen, and Yang Xiang. Security analysis on tangle-based blockchain through simulation. CoRR, abs/2008.04863, 2020. URL: http://arxiv.org/abs/2008.04863.
  31. Qin Wang, Jiangshan Yu, Zhiniang Peng, Van Cuong Bui, Shiping Chen, Yong Ding, and Yang Xiang. Security analysis on dbft protocol of NEO. In Financial Cryptography, volume 12059 of Lecture Notes in Computer Science, pages 20-31. Springer, 2020. Google Scholar
  32. Maofan Yin. Scaling the Infrastructure of Practical Blockchain Systems. PhD thesis, Cornell University, USA, 2021. Google Scholar
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