Stubborn Mining: Generalizing Selfish Mining and Combining with an Eclipse Attack
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!
2016 IEEE European Symposium on Security and Privacy (EuroS&P)