Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack

Kartik Nayak, Srijan Kumar, Andrew Edmund Miller, Elaine Shi

Research output: Contribution to conferencePaper

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)
Pages305-320
StatePublished - Mar 2016
Event2016 IEEE European Symposium on Security and Privacy (EuroS&P) - Saarbrucken, Germany
Duration: Mar 21 2016Mar 24 2016

Conference

Conference2016 IEEE European Symposium on Security and Privacy (EuroS&P)
CountryGermany
CitySaarbrucken
Period3/21/163/24/16

Keywords

  • lead
  • online banking
  • peer-to-peer computing
  • protocols
  • cryptography
  • computational modeling

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    Nayak, K., Kumar, S., Miller, A. E., & Shi, E. (2016). Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack. 305-320. Paper presented at 2016 IEEE European Symposium on Security and Privacy (EuroS&P), Saarbrucken, Germany.