Stubborn mining: Generalizing selfish mining and combining with an eclipse attack

Kartik Nayak, Srijan Kumar, Andrew Miller, Elaine Shi

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

Abstract

Selfish mining, originally discovered by Eyal et al. [9], is a well-known attack where a selfish miner, under certain conditions, can gain a disproportionate share of reward by deviating from the honest behavior. In this paper, we expand the mining strategy space to include novel "stubborn" strategies that, for a large range of parameters, earn the miner more revenue. Consequently, we show that the selfish mining attack is not (in general) optimal. Further, we show how a miner can further amplify its gain by non-trivially composing mining attacks with network-level eclipse attacks. We show, surprisingly, that given the attacker's best strategy, in some cases victims of an eclipse attack can actually benefit from being eclipsed!

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE European Symposium on Security and Privacy, EURO S and P 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages305-320
Number of pages16
ISBN (Electronic)9781509017515
DOIs
StatePublished - May 9 2016
Externally publishedYes
Event1st IEEE European Symposium on Security and Privacy, EURO S and P 2016 - Saarbruecken, Germany
Duration: Mar 21 2016Mar 24 2016

Publication series

NameProceedings - 2016 IEEE European Symposium on Security and Privacy, EURO S and P 2016

Other

Other1st IEEE European Symposium on Security and Privacy, EURO S and P 2016
CountryGermany
CitySaarbruecken
Period3/21/163/24/16

Keywords

  • Bitcoin
  • Selfish Mining

ASJC Scopus subject areas

  • Computer Networks and Communications

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