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CRYPTO2026Top-tier venue

Optimal Best-of-Both-Worlds Consensus

Fatima Elsheimy, Simon Holmgaard Kamp, Julian Loss, Jesper Buus Nielsen

2026Year

Abstract

Consensus protocols face a fundamental trade-off: synchrony enables higher fault tolerance, whereas asynchrony provides responsiveness (latency proportional to actual network delays) and security under arbitrary delays. In particular, synchronous consensus achieves optimal resilience up to t<n/2t<n/2 corruptions but relies on worst-case delay bounds that affect both latency and security, whereas asynchronous consensus tolerates only t<n/3t<n/3 corruptions.

Two approaches have sought orthogonal compromises between the two. Optimistically responsive protocols [Pass and Shi, EC'18] achieve resilience beyond the feasibility limits of asynchronous security, and provide responsiveness under optimistic conditions. Network-agnostic protocols [Blum–Katz–Loss, TCC'19] are secure in both synchronous and asynchronous networks but are non-responsive due to relying on conservative worst-case waiting and, to date, do not achieve constant time in asynchrony.

We reconcile these approaches by constructing the first Byzantine agreement (BA) and validated Byzantine agreement (VBA) protocols that achieve network-agnostic security and optimistic responsiveness with optimal resilience tradeoffs. Concretely, for thresholds ts>tr>tat_s > t_r > t_a satisfying n>2ts+tan > 2t_s + t_a and n>ts+2trn > t_s + 2t_r, our protocols satisfy: (1) Both protocols are synchronously secure for up to tst_s corruptions and asynchronously secure for up to tat_a corruptions. (2) Our VBA protocol is responsive when the number of corruptions is at most trt_r, while our BA protocol is responsive if additionally at least ts+1t_s+1 honest parties begin with the same input. (3) Both protocols run in expected constant time with quadratic communication complexity, regardless of network conditions.

We prove matching impossibility results showing that the resilience tradeoffs are optimal, and our protocols additionally achieve optimal expected time and communication complexity.

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