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Identifying Incentives for Extortion in Proof of Stake Consensus Protocols

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The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022) (DBB 2022)


A distributed consensus algorithm is at the core of what makes cryptocurrencies a decentralised ledger; they are the tools that facilitate the agreement between millions of users worldwide on what the playing rules are going to be, as well as the punishments and rewards for (dis)obeying them. The first cryptocurrency, Bitcoin, popularised proof-of-work puzzle-solving algorithm, in the form of block mining to process and validate transactions on the blockchain. However, several limitations with proof-of-work, such as enormous energy demand, significant (and increasing) computational power requirement, and lack of scalability, led blockchain enthusiasts and researchers to construct alternatives. One prominent alternative mechanism proposed is the proof-of-stake; a mechanism that does not rely on the mining power but the amount of stake owned by a node, allowing randomly selected validators to create blocks and verify blocks created by other validators. A proof-of-stake mechanism naturally results in the formation of staking pools, whereby multiple stakeholders can pool their resource to earn rewards. In this paper we explore the likely evolution of a competitive staking pool market. We pay particular attention to the importance of security. Staking pools could be subject to a range of attacks by malicious actors and so secure staking pools are essential for a well functioning proof-of-stake currency.

Research partly supported by Ethereum Foundation Grant #FY21-0378 ‘Game theoretic modelling of a ransomware attack on validators in Ethereum 2.0’.

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We thank Justin Drake from the Ethereum Foundation for his support and feedback throughout this research. The research of Alpesh Bhudia is supported by the EPSRC and the UK government as part of the Centre for Doctoral Training in Cyber Security at Royal Holloway, University of London (EP/P009301/1).

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Correspondence to Alpesh Bhudia .

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Bhudia, A., Cartwright, A., Cartwright, E., Hernandez-Castro, J., Hurley-Smith, D. (2023). Identifying Incentives for Extortion in Proof of Stake Consensus Protocols. In: Awan, I., Younas, M., Bentahar, J., Benbernou, S. (eds) The International Conference on Deep Learning, Big Data and Blockchain (DBB 2022). DBB 2022. Lecture Notes in Networks and Systems, vol 541. Springer, Cham.

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