FusionFedBlock: Fusion of blockchain and federated learning to preserve privacy in industry 5.0 br

Nowadays, Industries are experiencing rapid changes in the digital environment, referred to as Industry 5.0. The Internet of Things (IoT) and advanced technologies are essential in the industrial environment. Technological advancements can collect, transfer, and analyze vast amounts of data in the industry via promising technologies. Still, IoT has various issues when applied to industrial infrastructures, such as centralization, privacy preservation, latency, and security. This article proposes a scheme as FusionFedBlock: Fusion of Blockchain and Federated Learning to Preserve Privacy in Industry 5.0 to address the aforementioned issues. At the federated layer, the industry's departments (Production, Quality Control, Distribution) allow local learning updates with network automation and communicate to the global model, which miners verify in the Blockchain networks. Federated-Learning offers privacy preservation between various mentioned departments in industries. Decentralized secure storage is provided by the Distributed Hash Table (DHT) at the cloud layer. The validation outcomes of the proposed scheme demonstrate excellent performance as the accuracy of 93.5% in a 50% active node for Industry 5.0 compared to existing frameworks.

Automated summary

This article proposes a scheme called FusionFedBlock to address privacy issues in Industry 5.0 by combining blockchain and federated learning. In the scheme, industry departments can perform local learning updates and communicate with a global model, with validation conducted through a blockchain network. The scheme demonstrates excellent performance in privacy preservation and accuracy improvement.