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Optimal Block Withholding Strategies for Blockchain Mining Pools

IEEE TRANSACTIONS ON computational SOCIAL SYSTEMS 2020年第3期7卷 709-717页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266111 Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing 100190 Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Experiments & Parallel Syst Changsha 410073 Peoples R China Univ Chinese Acad Sci Ctr China Econ & Social Secur Beijing 100149 Peoples R China

In proof-of-work (PoW) consensus protocol-based blockchain mining, the pools can increase their rewards by utilizing block withholding attack. As such, how much computational power should be used to attack other pools becomes an important decision issue faced by the pools. This article mainly studies the block withholding attack issue faced by mining pools. Considering the case that there are two pools, where only one pool can attack the other pool, we propose an optimal block withholding strategies for pools. We also illustrate that attacking is not always the optimal strategies for the pools and present the conditions for attacking. With computational experiment approach, we designed several experiments to validate our proposed strategies, and our results can provide important managerial insights for pools in blockchain mining.

关键词： Games computational modeling Cryptography Automation Ecosystems Block withholding attack blockchain mining computational experiments approach pool mining

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A novel hybrid share reporting strategy for blockchain miners in PPLNS pools

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DECISION SUPPORT SYSTEMS 2019年 118卷 91-101页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Qingdao Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Changsha Hunan Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing Peoples R China

In blockchain pool mining, Pay-Per-Last-N-Shares (PPLNS) is one of the most commonly used reward mechanisms in practice, in which the mining pools will distribute the reward among the miners whose reported shares fall in the last N shares, according to the proportion of the number of shares of the miner in the last N shares. In the PPLNS mechanism, miners' reporting strategies may impose significant impacts to their rewards via determining the number of shares appeared in the last N shares. As such, how to strategically report their shares to the pool has become an important decision faced by miners. In this paper, we study the share reporting problem in PPLNS pools, and establish a share reporting model for a miner to optimize his/her rewards. We also propose a novel hybrid share reporting strategy for the miner based on our model, and design computational experiments to evaluate our hybrid share reporting strategy. The experimental results show that the hybrid strategy outperforms two baseline share reporting strategies commonly used in practice. This work is the first attempt to study the share reporting issue faced by miners in PPLNS pools, and it can provide important managerial insights for blockchain pool miners when making their share reporting decisions.

关键词： Share reporting strategy Blockchain mining PPLNS reward Pool mining computational experiments approach

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Optimal Share Reporting Strategies for Blockchain Miners in PPLNS Pools

Optimal Share Reporting Strategies for Blockchain Miners in ...

引用

IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Qingdao Peoples R China Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat Beijing Peoples R China Natl Univ Def Technol Res Ctr Mil Computat Expt & Parallel Syst Changsha Hunan Peoples R China

ISBN: (纸本)9781538666500

With the increasing difficulty of solo mining in blockchain mining, pool mining has become more and more popular, and most of the miners would like to join a mining pool and contribute their computational power to the pool. When the pool finds a valid block and get the reward from the blockchain network, it will distribute the reward to its miners according to its reward mechanism. In practice, the Pay-Per-Last-N-Shares (PPLNS) mechanism is one of the most commonly used mechanisms by pools, and the pool adopting PPLNS mechanism will distribute the reward to the miners whose reported shares are in the last N shares, according to their proportion of the number of shares in the last N shares. In the PPLNS mechanism, different reporting strategies may bring different rewards for miners. Thus, how to report their found shares to the pool has become an important issue faced by the miners. In this paper, we study the share reporting problem faced by the miners in PPLNS pools, and establish a share reporting optimization model for the miners. We also study the effect of the parameter N in the PPLNS mechanism on the optimal reporting strategies of the miners. With the computational experiments approach, we design experiments to evaluate our proposed share reporting strategies. This work is the first attempt to study the share reporting issue faced by miners in PPLNS pools, and it can provide useful managerial insights for miners when making their share reporting decisions in such pools.

关键词： share reporting strategy blockchain mining PPLNS reward pool mining computational experiments approach

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