Lightweight and privacy-aware decentralized identity management for Industrial Internet of Things applications

Next-generation industrial networks incorporate diverse devices and technologies, including cloud- and fog-based systems and large-scale Industrial Internet of Things (IIoT) applications. These heterogeneous environments comprise thousands of sensors, actuators, controllers, and geographically distributed zones, posing significant challenges for authentication mechanisms that must scale while remaining secure and practical under real industrial conditions. Current blockchain-based decentralized identity-management systems are characterized by high transaction overhead, reliance on computationally intensive cryptographic operations, and partial dependence on trusted entities, all of which limit their scalability and practical deployment. To address these issues, in this paper, we propose a lightweight, blockchain-based identity-management solution that integrates epoch- and batch-based registration with sparse Merkle trees (SMTs). Device registrations are grouped into fixed epochs, and cryptographic costs are amortized across multiple devices to substantially reduce per-device overhead. The SMT structure generates verifiable, reusable proofs that preserve privacy while enabling efficient verification; sensitive device information is never revealed during authentication. Fog nodes act as decentralized verifiers, supporting distributed trust without continuous interaction with the blockchain. Experimental results show that the system can be practically deployed on Raspberry Pi and ESP32 devices, reliably perform identification with around 1000 total messages, and operate at the tested upper bound of 7000 devices distributed over 20 fog nodes, all while keeping the blockchain storage overhead under 5 MB.