Attribute-Based Access Control Scheme for Secure Identity Resolution in Prognostics and Health Management

In modern industrial enterprises, the application of identity resolution systems contributes to improving efficiency and simplifying production management. With the development of the Industrial Internet of Things (IIoT), integrating identity resolution and Prognostics and Health Management (PHM) has become a new trend. However, ensuring the confidentiality and integrity of enterprise identity data has become challenging due to flaws in identifier encoding design and the semi-trusted nature of identity resolution platforms. To address these issues, we propose a fine-grained access control scheme for the identity resolution system. Our scheme utilizes a novel identifier encoding method and attribute-based encryption algorithm, enabling flexible data classification and permission management for industry enterprises. Moreover, to combat potential malicious behaviors by users, such as unauthorized access or identity abuse, we leverage Blockchain technology to trace malicious users while safeguarding user privacy. The security of our scheme is formally proven under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. Comparative experiments demonstrate the advantages of our proposal in terms of time costs and storage overhead over alternative schemes.