Blockchain-Based Federated Learning for Device Failure Detection in Industrial IoT

• Published in: IEEE internet of things journal Vol. 8; no. 7; pp. 5926 - 5937
• Main Authors: Zhang, Weishan, Lu, Qinghua, Yu, Qiuyu, Li, Zhaotong, Liu, Yue, Lo, Sin Kit, Chen, Shiping, Xu, Xiwei, Zhu, Liming
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Blockchain; Blockchains; Centroids; Collaboration; Computational modeling; Computer architecture; Cryptography; Data models; edge computing; Failure detection; Feasibility; Federated learning; Heterogeneity; Industrial applications; Industrial Internet of Things; Internet of Things; IoT; machine learning; Servers; Training

Device failure detection is one of most essential problems in Industrial Internet of Things (IIoT). However, in conventional IIoT device failure detection, client devices need to upload raw data to the central server for model training, which might lead to disclosure of sensitive business data. Ther...