Abstract

In current Proof-of-Work (PoW) blockchain systems, miners usually form mining pools to compete with other pools/miners in the mining competition. Forming pools can give miners steady revenues but will introduce two critical issues. One is mining pool selection, where miners select the pools to join in order to maximize their revenues. The other is a Block WithHolding (BWH) attack, where pools can inject part of their hash/mining power into other pools to obtain additional revenues without contributing to the mining process of the attacked pools. Reasoning that the BWH attack will have significant impacts on the pool selection, we therefore investigate the mining pool selection issue in the presence of a BWH attack in this paper. In particular, we model the pool selection process of miners as an evolutionary game and find the Evolutionarily Stable States (ESSs) of the game (i.e., stable pool population states) as the solutions. Previous studies investigated this problem from the perspective of pool managers and neglected the revenues from attacked pools (attacking revenues), leading to less accurate and insightful findings. This paper, however, focuses on the payoffs of miners and carefully takes the attacking revenues into consideration. To demonstrate how the problem is solved, we consider the scenario with two mining pools and further investigate the case where one pool attacks the other and the case where the two pools attack each other. The results in this paper show that pools can attract more miners to join by launching a BWH attack and the attack power significantly affects the stable pool populations.

Highlights

  • We investigate the impacts of the Block WithHolding (BWH) attack size on the stable population states

  • We have investigated the mining pool selection problem in the presence of a Block WithHolding (BWH) attack and obtained the stable population states from the perspective of evolutionary game theory

  • We have focused on the scenario with two mining pools and provided simulation and theoretical results to show the correctness of the analysis

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Summary

Introduction

Different from traditional centralized ledgers that reliably manage transactions in a central server, all participants in blockchain systems are synchronized to maintain the same copies of the transactions in order to guarantee the tamper-proof feature Such a feature renders blockchain a highly promising technology for cryptocurrency platforms, such as Bitcoin [1] and Ethereum [2], as well as other applications like cyber–physical systems [3], access control [4,5,6,7,8], supply chain management [9], data sharing [10] and storage [11], healthcare [12,13,14], real estate [15] and media digital right [16].

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