Secure Data Sharing and Prediction with Digital Twin and Blockchain in Healthcare

The rapid implementation of the fifth-generation wireless networks has driven advances in digital twin (DT) technique, which has been widely used, especially in healthcare. However, the accessibility of data raises concerns about privacy, security, and accountability among participants, affecting overall security and performance of the healthcare DT system. In this article, we investigate a blockchain-based secure healthcare digital twin data (HDTD) sharing framework to address data privacy concerns. In the blockchain-based secure HDTD sharing model, we propose the access control scheme through cloud storage and attribute encryption to realize the secure data interaction between different users. Based on this, we design an HDTD missing value prediction algorithm in order to solve the problem of missing valid data due to data tampering or loss with limited resources and to meet the real-time requirements of data interaction in DT. The experimental results show that compared with the existing schemes, the proposed blockchain-based secure HDTD sharing scheme has superior performance in improving data security and reducing data interaction delay. The article outlines key technical challenges and future directions for blockchain-based HDTD research.