Systematization of Knowledge: Formal Verification of Consensus Protocols

📅 2026-08-22
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
本文通过分析20多种共识协议,提出了一种统一的验证方法分类体系,旨在解决区块链共识协议中形式化验证方法碎片化的问题。
📝 Abstract
Formal verification is increasingly critical for blockchain consensus protocols, where subtle bugs can cause irreversible financial loss and network failure. Yet the literature on verification methods is fragmented across tools, protocol families, and property classes, hindering cumulative progress. This Systematization of Knowledge paper analyzes over 20 verified consensus protocols--from crash-fault-tolerant Raft to Byzantine-fault-tolerant HotStuff, DAG-based FairDAG, and proof-of-stake Beacon Chain--to establish a unified taxonomy of verification approaches. We introduce a verification maturity scale ranging from informal reasoning to machine-checked code proofs, and present a Protocol--Property--Method matrix mapping protocols to verified safety, liveness, and economic properties. Our analysis reveals persistent gaps: liveness verification remains underdeveloped despite its importance for progress guarantees; specification-implementation disconnects undermine real-world assurance; and scalability limits restrict verification to small networks. We provide practical recommendations for tool selection and proof engineering, and outline a research roadmap toward scalable, economically-aware verification. This work aims to guide both researchers and practitioners in building more rigorously verified consensus systems.
Problem

Research questions and friction points this paper is trying to address.

formal verification
consensus protocols
blockchain
liveness verification
scalability
Innovation

Methods, ideas, or system contributions that make the work stand out.

formal verification
consensus protocols
verification maturity scale
Protocol-Property-Method matrix
scalability
N
Nikita Bondarev
Skolkovo Institute of Science and Technology, Moscow, Russia; Lomonosov Moscow State University, Moscow, Russia
K
Kirill Ziborov
Positive Technologies, Moscow, Russia; Lomonosov Moscow State University, Moscow, Russia
Yury Yanovich
Yury Yanovich
Skolkovo Institute of Science and Technology
BlockchainStatisticsMachine learning