Abstract
Over the last few years, the interest in blockchain platforms has fostered the implementation of a number of distributed ledger-based solutions for the exchange of information, assets and digitized goods in both the private and the public sectors. While proposing promising alternatives to the original Bitcoin protocol is an important goal that the bulk of the effort in blockchain community has been focused on, it may not be enough. A major challenge faced by blockchain systems goes beyond the ability to superficially explore their attack surface, and firstly must consider the importance of studying the functioning of their underlying consensus protocols also in the form of non-functional properties such as security and safety. It is to this extent that recent research has started to rigorously analyze the Bitcoin protocol and its close variants, whilst BFT-like systems have not received equal attention so far. In this paper, we focus on the XRP Ledger with the aim to lay down the first steps towards the complete formalization of its unique consensus mechanism. We provide a thorough description of its different phases and present an analysis of some of its properties, which will be suitable as a basis for future research in the same vein.
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- 1.
The XRP Ledger is better known as “Ripple” because originally this was the name used to refer to the protocol. Recently, in order to differentiate it from the company, the term “XRP Ledger” has been adopted to refer to the technology.
- 2.
- 3.
- 4.
Even if it appears counterintuitive, in practice the open ledger is never really closed. When certain conditions are met, the validator throws away its open ledger, builds a new last closed ledger by starting with the prior last closed ledger, and then creates a new open ledger using the newly created last closed ledger as a basis.
- 5.
In the XRP Ledger network, the very first ledger started with ledger index 1. However, since in practice this is no longer available, the ledger \(\#32570\) is considered the actual genesis ledger.
References
Abraham, I., Malkhi, D.: The blockchain consensus layer and BFT. Bull. EATCS 3(123) (2017). http://eatcs.org/beatcs/index.php/beatcs/article/view/506
Armknecht, F., Karame, G.O., Mandal, A., Youssef, F., Zenner, E.: Ripple: Overview and Outlook. In: Conti, M., Schunter, M., Askoxylakis, I. (eds.) Trust 2015. LNCS, vol. 9229, pp. 163–180. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22846-4_10
Badertscher, C., Garay, J., Maurer, U., Tschudi, D., Zikas, V.: But why does it work? a rational protocol design treatment of bitcoin. In: Nielsen, J.B., Rijmen, V. (eds.) EUROCRYPT 2018. LNCS, vol. 10821, pp. 34–65. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-78375-8_2
Badertscher, C., Maurer, U., Tschudi, D., Zikas, V.: Bitcoin as a transaction ledger: a composable treatment. In: Katz, J., Shacham, H. (eds.) CRYPTO 2017. LNCS, vol. 10401, pp. 324–356. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63688-7_11
Bano, S., et al.: Consensus in the Age of Blockchains. CoRR abs/1711.03936 (2017). http://arxiv.org/abs/1711.03936
Braghin, C., Cimato, S., Cominesi, S.R., Damiani, E., Mauri, L.: Towards blockchain-based e-voting systems. In: Abramowicz, W., Corchuelo, R. (eds.) BIS 2019. LNBIP, vol. 373, pp. 274–286. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-36691-9_24
Braghin, C., Cimato, S., Damiani, E., Baronchelli, M.: Designing smart-contract based auctions. In: Yang, C.-N., Peng, S.-L., Jain, L.C. (eds.) SICBS 2018. AISC, vol. 895, pp. 54–64. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-16946-6_5
Cachin, C., Tackmann, B.: Asymmetric distributed trust. In: Felber, P., Friedman, R., Gilbert, S., Miller, A. (eds.) 23rd International Conference on Principles of Distributed Systems, OPODIS 2019, 17–19 December, 2019, Neuchâtel, Switzerland. LIPIcs, vol. 153, pp. 7:1–7:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2019). https://doi.org/10.4230/LIPIcs.OPODIS.2019.7
Cachin, C., Vukolic, M.: Blockchain Consensus Protocols in the Wild. CoRR abs/1707.01873 (2017). http://arxiv.org/abs/1707.01873
Cachin, C., Zanolini, L.: Asymmetric Byzantine Consensus. CoRR abs/2005.08795 (2020). https://arxiv.org/abs/2005.08795
Chase, B., MacBrough, E.: Analysis of the XRP Ledger Consensus Protocol. CoRR abs/1802.07242 (2018). http://arxiv.org/abs/1802.07242
Christodoulou, K., Iosif, E., Inglezakis, A., Themistocleous, M.: Consensus crash testing: exploring ripple’s decentralization degree in adversarial environments. Future Internet 12(3), 53 (2020)
Daian, P., Pass, R., Shi, E.: Snow White: Provably Secure Proofs of Stake. Cryptology ePrint Archive, Report 2016/919 (2016)
Damgård, I., Desmedt, Y., Fitzi, M., Nielsen, J.B.: Secure protocols with asymmetric trust. In: Kurosawa, K. (ed.) ASIACRYPT 2007. LNCS, vol. 4833, pp. 357–375. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76900-2_22
Fischer, M.J., Lynch, N.A., Paterson, M.S.: Impossibility of distributed consensus with one faulty process. J. ACM 32(2), 374–382 (1985). https://doi.org/10.1145/3149.214121
Garay, J., Kiayias, A., Leonardos, N.: The bitcoin backbone protocol: analysis and applications. In: Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS, vol. 9057, pp. 281–310. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46803-6_10
Garay, J., Kiayias, A., Leonardos, N.: The bitcoin backbone protocol with chains of variable difficulty. In: Katz, J., Shacham, H. (eds.) CRYPTO 2017. LNCS, vol. 10401, pp. 291–323. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63688-7_10
Garay, J.A., Kiayias, A., Leonardos, N., Panagiotakos, G.: Bootstrapping the blockchain, with applications to consensus and fast PKI setup. In: Abdalla, M., Dahab, R. (eds.) PKC 2018. LNCS, vol. 10770, pp. 465–495. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76581-5_16
García-Pérez, Á., Gotsman, A.: Federated byzantine quorum systems. In: Cao, J., Ellen, F., Rodrigues, L., Ferreira, B. (eds.) 22nd International Conference on Principles of Distributed Systems, OPODIS 2018, 17–19 December 2018, Hong Kong, China. LIPIcs, vol. 125, pp. 17:1–17:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018). https://doi.org/10.4230/LIPIcs.OPODIS.2018.17
Gramoli, V.: From blockchain consensus back to byzantine consensus. Future Gener. Comput. Syst. 107, 760–769 (2017)
Halpin, H., Piekarska, M.: Introduction to security and privacy on the blockchain. In: EuroS&P 2017 - 2nd IEEE European Symposium on Security and Privacy, Workshops, April 2017. https://doi.org/10.1109/EuroSPW.2017.43, https://hal.inria.fr/hal-01673293
Kiayias, A., Russell, A., David, B., Oliynykov, R.: Ouroboros: a provably secure proof-of-stake blockchain protocol. In: Katz, J., Shacham, H. (eds.) CRYPTO 2017. LNCS, vol. 10401, pp. 357–388. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-63688-7_12
Losa, G., Gafni, E., Mazières, D.: Stellar consensus by instantiation. In: Suomela, J. (ed.) 33rd International Symposium on Distributed Computing (DISC 2019). Leibniz International Proceedings in Informatics (LIPIcs), vol. 146, pp. 27:1–27:15. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany (2019). https://doi.org/10.4230/LIPIcs.DISC.2019.27, http://drops.dagstuhl.de/opus/volltexte/2019/11334
Malkhi, D., Nayak, K., Ren, L.: Flexible Byzantine Fault Tolerance. In: Cavallaro, L., Kinder, J., Wang, X., Katz, J. (eds.) Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, CCS 2019, London, UK, 11–15 November 2019, pp. 1041–1053. ACM (2019). https://doi.org/10.1145/3319535.3354225
Malkhi, D., Reiter, M.K.: Byzantine quorum systems. In: Leighton, F.T., Shor, P.W. (eds.) Proceedings of the 29th Annual ACM Symposium on the Theory of Computing, El Paso, Texas, USA, 4–6 May 1997, pp. 569–578. ACM (1997). https://doi.org/10.1145/258533.258650
Mauri, L., Cimato, S., Damiani, E.: A comparative analysis of current cryptocurrencies. In: Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, pp. 127–138. INSTICC, SciTePress (2018). https://doi.org/10.5220/0006648801270138
Mauri, L., Cimato, S., Damiani, E.: A Formal Approach for the Analysis of the XRP Ledger Consensus Protocol. In: Furnell, S., Mori, P., Weippl, E.R., Camp, O. (eds.) Proceedings of the 6th International Conference on Information Systems Security and Privacy, ICISSP 2020, Valletta, Malta, 25–27 February 2020, pp. 52–63. SCITEPRESS (2020). https://doi.org/10.5220/0008954200520063
Nakamoto, S.: Bitcoin: A Peer-to-Peer Electronic Cash System (2008). https://bitcoin.org/bitcoin.pdf
Pass, R., Seeman, L., Shelat, A.: Analysis of the blockchain protocol in asynchronous networks. In: Coron, J.-S., Nielsen, J.B. (eds.) EUROCRYPT 2017. LNCS, vol. 10211, pp. 643–673. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56614-6_22
Pass, R., Shi, E.: The sleepy model of consensus. In: Takagi, T., Peyrin, T. (eds.) ASIACRYPT 2017. LNCS, vol. 10625, pp. 380–409. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70697-9_14
Pease, M., Shostak, R., Lamport, L.: Reaching agreement in the presence of faults. J. ACM 27(2), 228–234 (1980)
Pérez, D., Xu, J., Livshits, B.: We Know What They’ve Been Put Through: Revisiting High-scalability Blockchain Transactions. CoRR abs/2003.02693 (2020). https://arxiv.org/abs/2003.02693
Rawat, D.B., Chaudhary, V., Doku, R.: Blockchain: Emerging Applications and Use Cases. CoRR abs/1904.12247 (2019). http://arxiv.org/abs/1904.12247
Ripple Labs Inc.: Ripple. https://ripple.com/ (a), https://ripple.com/. Accessed 01 June 2020
Ripple Labs Inc.: XRP Ledger Dev Portal. https://xrpl.org/index.html (b), https://xrpl.org/index.html. Accessed 01 June 2020
Ripple Labs Inc.: Ripple Source, GitHub repository. https://github.com/ripple/rippled/tree/develop/src/ripple (c), https://github.com/ripple/rippled/tree/develop/src/ripple. Accessed 01 June 2020
Saad, M., et al.: Exploring the Attack Surface of Blockchain: A Systematic Overview. CoRR abs/1904.03487 (2019). http://arxiv.org/abs/1904.03487
Schwartz, D., Youngs, N., Britto, A.: The Ripple Protocol Consensus Algorithm. Ripple Labs Inc., White Paper (2014). https://ripple.com/files/ripple_consensus_whitepaper.pdf
Vukolic, M.: The origin of quorum systems. Bull. EATCS 101, 125–147 (2010). http://eatcs.org/beatcs/index.php/beatcs/article/view/183
Vukolić, M.: The quest for scalable blockchain fabric: proof-of-work vs. BFT replication. In: Camenisch, J., Kesdoğan, D. (eds.) iNetSec 2015. LNCS, vol. 9591, pp. 112–125. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39028-4_9
Wang, W., et al.: A Survey on Consensus Mechanisms and Mining Management in Blockchain networks. CoRR abs/1805.02707 (2018). http://arxiv.org/abs/1805.02707
Wilson, B.: Raise quorum/increase fault tolerance, June 2018. https://github.com/ripple/rippled/issues/2604. Accessed 01 Oct 2019
Xiao, Y., Zhang, N., Lou, W., Hou, Y.T.: A Survey of Distributed Consensus Protocols for Blockchain Networks. CoRR abs/1904.04098 (2019). http://arxiv.org/abs/1904.04098
Acknowledgment
This work has been partly supported by the EC within the Project CONCORDIA (H2020-830927).
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Mauri, L., Cimato, S., Damiani, E. (2022). Untangling the XRP Ledger: Insights and Analysis. In: Furnell, S., Mori, P., Weippl, E., Camp, O. (eds) Information Systems Security and Privacy. ICISSP 2020. Communications in Computer and Information Science, vol 1545. Springer, Cham. https://doi.org/10.1007/978-3-030-94900-6_3
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