Construction of Secure Data Sharing Strategies and Incentive Mechanisms for Industrial Internet of Things Based on Digital Twin

This paper presents a secure data sharing strategy and incentive mechanism for the Industrial Internet of Things (IIoT) based on digital twin technology. As IIoT systems rely on real-time data exchange among heterogeneous and distributed devices, concerns about data privacy, ownership, and cybersecurity are increasingly critical. Digital twin offer a dynamic virtual representation of physical assets, enabling secure and efficient data tracking and validation. To address the reluctance of stakeholders in sharing data, a game-theoretic incentive model is proposed to promote active and trustworthy participation. The proposed framework ensures data integrity, confidentiality, and traceability while optimizing collaboration across the IIoT network. Experimental results and simulations validate the feasibility and effectiveness of the approach in enhancing secure data sharing and motivating stakeholders. This study contributes to bridging the gap between IIoT data security and economic motivation, laying a foundation for future intelligent and secure industrial ecosystems.