Abstract
Due to the open and dynamic nature of blockchain systems, the participants (users and miners) have to take into accounts uncertain constraints (e.g., the transaction confirmation times, the delays in the network, and the topology of the network) during their decision-making processes for carefully balancing their objectives. One of these objectives is to operate in a fair environment. This is important since participants may decide to leave the system if they cannot satisfy this objective, which may imply reduced security and sustainability of the system. Yet, existing approaches to modelling fairness are based on formalisms that do not capture the open and complex nature of the blockchain systems. In this paper, we discuss the current status of modelling of fairness based on a high-level description of blockchains and we exploit multi-agent modelling of fairness for users and miners.
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Notes
- 1.
Lightning Network, https://lightning.network, last access on 24 March 2019.
- 2.
Technically the miners can create empty blocks and get block rewards. But this is not the purpose of blockchain systems.
- 3.
Although it is open system and we can expect that participants may come back in the future, once they lose their trust it is harder to expect them to come back.
References
Alzahrani, N., Bulusu, N.: Block-supply chain: a new anti-counterfeiting supply chain using NFC and blockchain. In: Proceedings of the 1st Workshop on Cryptocurrencies and Blockchains for Distributed Systems, CryBlock 2018, pp. 30–35. ACM, New York (2018). https://doi.org/10.1145/3211933.3211939
Androulaki, E., et al.: Hyperledger fabric: a distributed operating system for permissioned blockchains. In: EuroSys 2018, Porto, Portugal, April 2018
Buchman, E., Kwon, J., Milosevic, Z.: The latest gossip on BFT consensus. arXiv preprint arXiv:1807.04938 (2018)
Carlsten, M., Kalodner, H., Weinberg, S.M., Narayanan, A.: On the instability of bitcoin without the block reward. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, pp. 154–167. ACM (2016)
Eyal, I., Sirer, E.G.: Majority is not enough: bitcoin mining is vulnerable. In: Christin, N., Safavi-Naini, R. (eds.) FC 2014. LNCS, vol. 8437, pp. 436–454. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45472-5_28
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
Goodman, L.M.: A self-amending crypto-ledger. Tezos white paper (2014)
Gürcan, Ö., Del Pozzo, A., Tucci-Piergiovanni, S.: On the bitcoin limitations to deliver fairness to users. In: Panetto, H., et al. (eds.) OTM 2017. LNCS, vol. 10573, pp. 589–606. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69462-7_37
Gürcan, Ö., Ranchal Pedrosa, A., Tucci-Piergiovanni, S.: On cancellation of transactions in bitcoin-like blockchains. In: Panetto, H., Debruyne, C., Proper, H.A., Ardagna, C.A., Roman, D., Meersman, R. (eds.) OTM 2018. LNCS, vol. 11229, pp. 516–533. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02610-3_29
Herlihy, M.: Atomic cross-chain swaps. In: Proceedings of the 2018 ACM PODC 2018, pp. 245–254. ACM, New York (2018)
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. IACR Cryptology ePrint Archive 2016, 454 (2016)
Pass, R., Shi, E.: Fruitchains: a fair blockchain. Cryptology ePrint Archive, Report 2016/916 (2016). http://eprint.iacr.org/2016/916.pdf
Pedrosa, A.R., Potop-Butucaru, M., Tucci-Piergiovanni, S.: Scalable lightning factories for bitcoin. In: SAC DADS (2019, to appear)
Russell, S.J., Norvig, P.: Artificial Intelligence - A Modern Approach, 3rd edn. Pearson Education, London (2010)
Sapirshtein, A., Sompolinsky, Y., Zohar, A.: Optimal selfish mining strategies in bitcoin. In: Grossklags, J., Preneel, B. (eds.) FC 2016. LNCS, vol. 9603, pp. 515–532. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-662-54970-4_30
Serugendo, G.D.M., Gleizes, M.P., Karageorgos, A. (eds.): Self-organising Software - From Natural to Artificial Adaptation. NCS. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-17348-6
Wang, W., et al.: A survey on consensus mechanisms and mining strategy management in blockchain networks. IEEE Access 7, 22328–22370 (2019). https://doi.org/10.1109/ACCESS.2019.2896108
Wood, G.: Ethereum: a secure decentralised generalised transaction ledger (2014). http://bitcoinaffiliatelist.com/wp-content/uploads/ethereum.pdf
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Gürcan, Ö. (2019). Multi-Agent Modelling of Fairness for Users and Miners in Blockchains. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_8
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