Abstract: Artificial intelligence is combined with the Internet of Things(IoT) to enhance application usage.In the IoT,data sharing can improve the quality of applications,but it also brings data security issues,such as data leakage and inability to verify du-ring the sharing process.This paper proposes a scheme combining distributed federated learning with blockchain and encryption verification to protect the privacy and effectiveness of shared data in the IoT.First,federated learning and blockchain are used to transform the direct sharing of original data into shared encryption model parameters in the IoT.Next,this paper proposes a method with encryption verification to verify and select on chain parameters during the model aggregation stage.Finally,the proposed method is compared with other methods,and experimental results show that our method can effectively ensure data privacy and achieve verification of encrypted data,ensuring the accuracy of the final model,and providing guarantees for high-quality data sharing in the IoT.

Key words: Federated learning, Blockchain, Internet of Things, Cryptographic verification, Homomorphic encryption