The widespread application of medical information systems has promoted the growth of personal electronic medical records (EMRs), which are typically produced in different medical institutions and stored in data centers. Consequently, data owners no longer retain control over their medical data, nor can they establish access control rules for their EMRs. Therefore, this study designs a patient-centered EMR access control system that integrates decentralized smart contracts and role-based access control (RBAC) to provide fine-grained data access control. In this system, we integrate a role-based access control model to achieve user-permission definition and adopt a personalized data access policy definition mechanism to achieve patient-centered data access control. The proposed system allows data owners to define a series of data access policies through smart contracts, achieving decentralized management of data access control permissions. In addition, we analyze the security features of this scheme and design a series of comparative experiments to evaluate the performance. The experimental results show that this system can efficiently achieve access control of personal electronic medical records and has higher reliability compared to traditional cloud-based EMR sharing systems.

In recent years, the refinements in industrial processes and the increasing complexity of managing privacy-sensitive data from Industrial Internet of Things (IIoT) devices, have highlighted the critical need for secure, robust, and adaptive data management solutions. In this work, we propose a smart contract-assisted access control scheme for IIoT, which employs the Attribute-Based Access Control (ABAC) model to set access permissions for different industrial components. We defined a storage model and data format for private data through the design and deployment of smart contracts to manage system operations and access policies. In addition, the bloom filter component is deployed to optimize the efficiency of contract management and system performance. Experimental results show that in the real-world simulations, Hyper-IIoT shows well-controlled contract execution time, stable system throughput and fast consensus process, and is capable of handling high throughput and effective consensus in distributed systems even in large-scale request scenarios.

In recent years, traditional logistics systems are developing toward intelligence based on the Internet of Things (IoT). Sensing devices throughout the logistics network provide strong support for smart logistics. However, due to the insufficient local computing and storage resources of IoT devices, logistics records with sensitive information are generally stored in a centralized cloud center, which could easily cause privacy leakage. In this study, we propose a blockchain-assisted secure storage scheme for logistics data. To be specific, this scheme can be briefly divided into two parts. The first part involves data generation and aggregation, session establishing, records encryption and storage, wherein a blockchain network is used to assist the cloud server with data storage, and smart contracts are deployed to provide reliable storage interfaces. In the second part, an efficient consensus mechanism is introduced to improve the efficiency of the consensus process. Also, the stored records can be securely audited by leveraging the deployed blockchain network. Finally, we analyze the security and privacy properties of this scheme and evaluate its performance in terms of computation and communication overhead by developing an experimental platform. The experimental results indicate that the performance of our scheme is acceptable.