most citedBFTBrain: Adaptive BFT Consensus with Reinforcement Learning

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

cs.DC2026

Flamingo: On Load Balancing in DAG-based Consensus Protocols

Zhen Ping Khor, Garvit Gupta, Mohammad Javad Amiri +1

Distributed data management systems deployed in untrusted environments rely on Byzantine Fault-Tolerant (BFT) consensus protocols to tolerate malicious failures. DAG-based BFT prot…

cs.CR2026

EVAGE: Autonomous MEV Generation and Adaptation via Multi-Agent Harness

Yan Wen, Zichun Cai, Iliya Mirzaei +4

Maximal Extractable Value (MEV) has evolved into a major economic force in blockchain ecosystems, yet its capture is dominated by experienced teams, and both strategy design and im…

cs.CR2026

Competition, Collusion, and Corruption: The Spectrum of MEV Attacks on DAG-Based BFT Consensus Protocols

Iliya Mirzaei, Heer Patel, Chenyuan Wu +1

Byzantine Fault-Tolerant (BFT) protocols guarantee safety and liveness despite the malicious failure of nodes. However, they do not prevent adversarial manipulation of transaction…

cs.DC2026

Fair on the Surface: Transaction-Ordering Bias and MEV in Mysticeti DAG-based BFT Protocol

Iliya Mirzaei, Mohammad Javad Amiri

Distributed systems deployed in untrustworthy environments agree on a common transaction order through Byzantine fault-tolerant (BFT) consensus protocols, and that order has real f…

cs.DC2026

AutoPilot: Learning to Steer High Speed Robust BFT

Liangrong Chen, Yue Zhang, Eric Zhou +3

Recent Byzantine Fault Tolerant (BFT) protocols achieve strong performance by combining the low-latency advantages of leader-based BFT protocols with the high-throughput benefits o…

cs.DC2024★ 1 cited

BFTBrain: Adaptive BFT Consensus with Reinforcement Learning

Chenyuan Wu, Haoyun Qin, Mohammad Javad Amiri +3

This paper presents BFTBrain, a reinforcement learning (RL) based Byzantine fault-tolerant (BFT) system that provides significant operational benefits: a plug-and-play system suita…