Adaptive Federated Blockchain-powered Security for MEC-assisted Industrial IoT Ecosystems

Secure communication is essential for the Industrial Internet of Things (IIoT), but most IIoT devices cannot run conventional security models due to resource constraints. Multi-access mobile edge computing (MEC) brings computational resources closer to the network edge but struggles with scalability and flexibility in centralized security solutions. Distributed data processing on MEC servers also raises privacy and security concerns. This paper proposes a novel IIoT network security using federated blockchain (FB) and machine learning-based (ML) verification. MEC optimizes the FB model to ensure data integrity and confidentiality between the IIoT's local network cluster and external devices. Data within the local network cluster are secured with public-key cryptography. The ML-based verification model ensures legitimate key-pair updates and device joining in MEC-assisted IIoT. This approach outperforms conventional security solutions in scalability, data privacy, and adaptability to IIoT network changes. We present a detailed implementation and evaluate its performance using a realistic IoT testbed, showing improved network security while maintaining the performance and scalability of MEC-assisted IIoT systems.