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Blockchain has become a popular decentralized paradigm for variousapplications in the zero-trust environment. The core of the blockchain is theconsensus protocol, which establishes consensus among all the participants. PoW(Proof-of-Work) is one of the most popular consensus protocols. However, thePoW consensus protocol which incentives the participants to use their computingpower to solve a meaningless hash puzzle is continuously questioned asenergy-wasting. To address these issues, we propose an efficient and secureconsensus protocol based on proof of useful federated learning for blockchain(called FedChain). We first propose a secure and robust blockchain architecturethat takes federated learning tasks as proof of work. Then a pool aggregationmechanism is integrated to improve the efficiency of the FedChain architecture.To protect model parameter privacy for each participant within a mining pool, asecret sharing-based ring-all reduce architecture is designed. We alsointroduce a data distribution-based federated learning model optimizationalgorithm to improve the model performance of FedChain. At last, azero-knowledge proof-based federated learning model verification is introducedto preserve the privacy of federated learning participants while proving themodel performance of federated learning participants. Our approach has beentested and validated through extensive experiments, demonstrating itsperformance.

FedChain: An Efficient and Secure Consensus Protocol based on Proof of Useful Federated Learning for Blockchain