Design of Secure and Scalable Industrial IoT Architecture Using Private 5G/6G Networks, Dynamic Network Slicing, Edge Intelligence, and Advanced PKI for Multi-Factory Environments

Abstract

The Industrial Internet of Things (IIoT) has become a fundamental enabler of Industry 4.0 and Industry 5.0, supporting intelligent manufacturing, predictive maintenance, digital twins, and autonomous industrial operations. However, large-scale industrial deployments continue to face significant challenges related to cybersecurity, scalability, latency, trust management, and interoperability. This paper proposes a secure and scalable end-to-end Industrial IoT architecture integrating Private 5G/6G networks, dynamic network slicing, edge intelligence, advanced Public Key Infrastructure (PKI), and artificial intelligence-driven security analytics for multi-factory environments. The architecture consists of six interconnected layers including Industrial Devices, Edge Intelligence, Private 5G/6G Access Networks, Cloud-Native Core Networks, Security and Trust Management, and Multi-Factory Orchestration. A PKI-based trust framework enables secure device onboarding, certificate lifecycle management, and zero-touch provisioning. Dynamic network slicing provides differentiated Quality of Service (QoS) for URLLC, mMTC, and eMBB industrial applications. A federated-learning-based GNN-GRU security engine supports real-time anomaly detection and automated threat response. Simulation-based evaluation using NS-3, UERANSIM, and OMNeT++ demonstrates improvements in latency, throughput, slice isolation, scalability, and cybersecurity performance compared with conventional industrial networking architectures. The proposed framework provides a practical roadmap for secure industrial digital transformation and future migration toward 6G-enabled industrial ecosystems.