Abstract
The paper presents a mathematical description of the vote delegation incentive process for funding proposals in a decentralized governance system using a blockchain-based voting. Two models of bribing a delegate by a proposer submitting proposals for funding are considered: “Rational Delegates” and “Emotional Delegates”. In terms of parameters describing the voting process, a sufficient condition for a Nash equilibrium is found to be as follows: if both a proposer and a delegate do not intend to participate in bribery. Moreover, it is shown at what share of the briber’s stake this condition is satisfied. The main practical result of the paper is the possibility to define what kind of an attacker (in terms of the bribing capability) we will be able to resist under certain parameters.
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References
Understanding dash governance (2021). https://docs.dash.org/en/stable/governance/understanding.html
Create, fund and deliver the future of cardano (2022). https://cardano.ideascale.com/
Fund your project with catalyst (2022). https://developers.cardano.org/docs/governance/project-catalyst
Allombert, V., Bourgoin, M., Tesson, J.: Introduction to the tezos blockchain. In: 2019 International Conference on High Performance Computing & Simulation (HPCS), pp. 1–10. IEEE (2019)
Balogun, H.O.: Towards sustainable blockchains: cryptocurrency treasury and general decision-making systems with provably secure delegable blockchain-based voting. Lancaster University (United Kingdom) (2021)
Birmpas, G., Kovalchuk, L., Lazos, P., Oliynykov, R.: Parallel contests for crowdsourcing reviews: existence and quality of equilibria. arXiv preprint arXiv:2202.04064 (2022)
Brandt, F., Sandholm, T.: Decentralized voting with unconditional privacy. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 357–364 (2005)
Brandt, F., Conitzer, V., Endriss, U., Lang, J., Procaccia, A.D.: Handbook of Computational Social Choice. Cambridge University Press, Cambridge (2016)
Dal Bó, E., Dal Bó, P., Di Tella, R.: “plata o plomo?”: bribe and punishment in a theory of political influence. Am. Polit. Sci. Rev. 100(1), 41–53 (2006)
Jafar, U., Aziz, M.J.A., Shukur, Z.: Blockchain for electronic voting system - review and open research challenges. Sensors 21(17) (2021). https://www.mdpi.com/1424-8220/21/17/5874. ISSN 1424–8220
Jairam, S., Gordijn, J., da Silva Torres, I., Kaya, F., Makkes, M.: A decentralized fair governance model for permissionless blockchain systems. In: Proceedings of the International Workshop on Value Modelling and Business Ontologies, pp. 4–5 (2021)
Kaidalov, D., Kovalchuk, L., Nastenko, A., Rodinko, M., Shevtsov, O., Oliynykov, R.: Ethereum classic treasury system proposal. IOHK RESEARCH REPORT (2017)
Kiayias, A., Lazos, P.: SoK: blockchain governance. arXiv preprint arXiv:2201.07188 (2022)
Kurbatov, O., et al.: Anonymous decentralized e-voting system. In: CMiGIN, pp. 12–22 (2019)
Lianju, S., Luyan, P.: Game theory analysis of the bribery behavior. Int. J. Bus. Soc. Sci. 2(8) (2011)
Liebkind, J.: How blockchain technology can prevent voter fraud, December 2020. https://www.investopedia.com/news/how-blockchain-technology-can-prevent-voter-fraud/
Zhang, B., Oliynykov, R., Balogun, R.: A treasury system for cryptocurrencies: enabling better collaborative intelligence. Cryptology ePrint Archive (2018)
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We gratefully thank Philip Lazos for fruitful discussions.
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Kovalchuk, L., Rodinko, M., Oliynykov, R. (2023). A Game-Theoretic Analysis of Delegation Incentives in Blockchain Governance. In: Garcia-Alfaro, J., Navarro-Arribas, G., Dragoni, N. (eds) Data Privacy Management, Cryptocurrencies and Blockchain Technology. DPM CBT 2022 2022. Lecture Notes in Computer Science, vol 13619. Springer, Cham. https://doi.org/10.1007/978-3-031-25734-6_17
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