Distributed systems handle adversarial nodes through redundancy, which imposes a significant performance overhead. In blockchain systems, Byzantine fault-tolerant state-machine replication (BFT-SMR) is the replicated service that totally orders client transactions before execution. While prior research has primarily focused on designing novel consensus algorithms with improved performance, recent studies have shown that further gains can be achieved through configuration optimization. More precisely, replicas can monitor network latency to dynamically assign the leader role and tune voting weights, thereby improving consensus performance. However, we identify three vulnerabilities in this process that Byzantine nodes can exploit. To address these weaknesses, we propose Beware, a reconfiguration framework that filters out falsified latency reports, computes robust weight distributions, and applies machine learning to converge towards Byzantine-resilient configurations. Our evaluation shows that Beware reduces consensus latency by up to 45% compared to existing solutions.

翻译：分布式系统通过冗余机制处理恶意节点，但这会带来显著的性能开销。在区块链系统中，拜占庭容错状态机复制（BFT-SMR）是一种在执行前对客户端交易进行全序排列的复制服务。尽管以往研究主要关注设计性能更优的新型共识算法，但近年研究表明，通过配置优化可实现进一步的性能提升。具体而言，副本可监控网络延迟来动态分配领导者角色并调整投票权重，从而改善共识性能。然而，我们在此过程中发现了三种可被拜占庭节点利用的漏洞。针对这些缺陷，我们提出Beware重配置框架，该框架能过滤虚假延迟报告、计算鲁棒权重分布，并运用机器学习收敛至抗拜占庭配置。评估表明，与现有解决方案相比，Beware可将共识延迟降低高达45%。