Consistency of Proof-of-Stake Blockchains with Concurrent Honest Slot Leaders

Abstract

We improve the fundamental security threshold of eventual consensus Proof-of-Stake (PoS) blockchain protocols under the longest-chain rule by showing, for the first time, the positive effect of rounds with concurrent honest leaders. Current security analyses reduce consistency to the dynamics of an abstract, round-based block creation process that is determined by three events associated with a round: (i) event AA: at least one adversarial leader, (ii) event SS: a single honest leader, and (iii) event MM: multiple, but honest, leaders. We present an asymptotically optimal consistency analysis assuming that an honest round is more likely than an adversarial round (i.e., Pr[S]+Pr[M]>Pr[A]\Pr[S] + \Pr[M] > \Pr[A]); this threshold is optimal. This is a first in the literature and can be applied to both the simple synchronous communication as well as communication with bounded delays. In all existing consistency analyses, event MM is either penalized or treated neutrally. Specifically, the consistency analyses in Ouroboros Praos (Eurocrypt 2018) and Genesis (CCS 2018) assume that Pr[S]Pr[M]>Pr[A]\Pr[S] - \Pr[M] > \Pr[A]; the analyses in Sleepy Consensus (Asiacrypt 2017) and Snow White (Fin. Crypto 2019) assume that Pr[S]>Pr[A]\Pr[S] > \Pr[A]. Moreover, all existing analyses completely break down when Pr[S]<Pr[A]\Pr[S] < \Pr[A]. These thresholds determine the critical trade-off between the honest majority, network delays, and consistency error. Our new results can be directly applied to improve the security guarantees of the existing protocols. We also provide an efficient algorithm to explicitly calculate these error probabilities in the synchronous setting. Furthermore, we complement these results by analyzing the setting where SS is rare, even allowing Pr[S]=0\Pr[S] = 0, under the added assumption that honest players adopt a consistent chain selection rule.Comment: Includes new sections describing (1) an adaptive online adversary and (2) an efficient algorithm to compute consistency error probabilities. arXiv admin note: text overlap with arXiv:1911.1018

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