Undetectable Selfish Mining

Maryam Bahrani, S. Matthew Weinberg

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Seminal work of Eyal and Sirer [2014] establishes that a strategic Bitcoin miner may strictly profit by deviating from the intended Bitcoin protocol, using a strategy now termed selfish mining. More specifically, any miner with > 1/3 of the total hashrate can earn bitcoin at a faster rate by selfish mining than by following the intended protocol (depending on network conditions, a lower fraction of hashrate may also suffice). One convincing critique of selfish mining in practice is that the presence of a selfish miner is statistically detectable: the pattern of orphaned blocks created by the presence of a selfish miner cannot be explained by natural network delays. Therefore, if an attacker chooses to selfish mine, users can detect this, and this may (significantly) negatively impact the value of BTC. So while the attacker may get slightly more bitcoin by selfish mining, these bitcoin may be worth significantly less USD. We develop a selfish mining variant that is provably statistically undetectable: the pattern of orphaned blocks is statistically identical to a world with only honest miners but higher network delay. Specifically, we consider a stylized model where honest miners with network delay produce orphaned blocks at each height independently with probability β. We propose a selfish mining strategy that instead produces orphaned blocks at each height independently with probability β > β. We further show that our strategy is strictly profitable for attackers with 38.2% ≪ 50% of the total hashrate (and this holds for all natural orphan rates β).

Original languageEnglish (US)
Title of host publicationEC 2024 - Proceedings of the 25th Conference on Economics and Computation
PublisherAssociation for Computing Machinery, Inc
Pages1017-1044
Number of pages28
ISBN (Electronic)9798400707049
DOIs
StatePublished - Dec 17 2024
Event25th Conference on Economics and Computation, EC 2024 - New Haven, United States
Duration: Jul 8 2024Jul 11 2024

Publication series

NameEC 2024 - Proceedings of the 25th Conference on Economics and Computation

Conference

Conference25th Conference on Economics and Computation, EC 2024
Country/TerritoryUnited States
CityNew Haven
Period7/8/247/11/24

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Economics and Econometrics
  • Computational Mathematics
  • Statistics and Probability

Keywords

  • blockchain
  • cryptocurrency
  • proof-of-work
  • selfish mining

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