Byzantine Fault Tolerance

Byzantine Fault Tolerance (BFT) focuses on designing distributed systems that function correctly even when some participants (nodes) behave maliciously or fail unpredictably. Current research emphasizes developing efficient BFT algorithms for federated learning, particularly focusing on decentralized architectures and robust aggregation methods like Krum and gradient clipping to mitigate the impact of faulty nodes. This work is crucial for securing distributed applications like AI training and multi-robot systems, ensuring reliable operation and preventing data corruption or manipulation by malicious actors. The resulting improvements in robustness and security have significant implications for various fields relying on distributed computation.