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Research Article | Open Access

The impact of network delay on Nakamoto consensus mechanism

Shaochen Lin1Xuyang Liu1Xiujuan Ma3Hongliang Mao3Zijian Zhang1,2( )Salabat Khan4Liehuang Zhu1( )
School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Southeast Institute of Information Technology, Beijing Institute of Technology, Fujian 351100, China
National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China
School of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
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Abstract

Nakamoto consensus is prevailing in the world largest blockchain-based cryptocurrency systems, such as Bitcoin and Ethereum. Since then, various attempts have been studied to attack Nakamoto consensus worldwide. In recent years, network delay has won more attention for making inconsistent ledgers in blockchain-based applications by virtue of attacking Nakamoto consensus. However, so far as we know, most of the existing works mainly focus on constructing inconsistent ledgers for blockchain systems, but not offering fine-grained theoretical analysis for how to optimize the success probability by flexibly dividing computational power and network delay from the viewpoint of adversary. The paper first utilizes network delay and the partition of controlled computation power of honest miners for making forks as long as possible. Then, formally analysis is provided to show the success probability of the proposed attack, and compute the optimal network delay and splitting for adversarial computation power in theory. Finally, simulation experiments validate the correctness of the formal analysis.

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Electronic Research Archive
Pages 3735-3754

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Cite this article:
Lin S, Liu X, Ma X, et al. The impact of network delay on Nakamoto consensus mechanism. Electronic Research Archive, 2022, 30(10): 3735-3754. https://doi.org/10.3934/era.2022191

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Received: 30 May 2022
Revised: 19 July 2022
Accepted: 27 July 2022
Published: 15 October 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)