Traditional cloud-centric approaches to medical data sharing pose risks related to real-time performance, security, and stability. Medical and healthcare data encounter challenges like data silos, privacy breaches, and transmission latency. In response to these challenges, this paper introduces a blockchain-based framework for trustworthy medical data sharing in edge computing environments. Leveraging healthcare consortium edge blockchains, this framework enables fine-grained access control to medical data. Specifically, it addresses the real-time, multi-attribute authorization challenge in CP-ABE through a Distributed Attribute Authorization strategy (DAA) based on blockchain. Furthermore, it tackles the key security issues in CP-ABE through a Distributed Key Generation protocol (DKG) based on blockchain. To address computational resource constraints in CP-ABE, we enhance a Distributed Modular Exponentiation Outsourcing algorithm (DME) and elevate its verifiable probability to “1”. Theoretical analysis establishes the IND-CPA security of this framework in the Random Oracle Model. Experimental results demonstrate the effectiveness of our solution for resource-constrained end-user devices in edge computing environments.
Conventional blockchain consensus protocols tailored for the Internet of Vehicles (IoV) usually face low transaction throughput, high latency, and elevated communication overhead issues. To address these issues, in this paper, we propose ESBCP, an efficient and secure blockchain consensus protocol for the IoV environment. Firstly, considering the significant performance differences among nodes in the IoV, we designed a blockchain consensus model for the IoV. Roadside units execute a trust evaluation mechanism to select high-quality vehicle nodes for the consensus process, thereby reducing the likelihood of malicious nodes in the consensus cluster. Secondly, we designed a node partition strategy to adapt to the dynamic feature of the IoV. Finally, addressing the mobility of nodes in the IoV, we introduced a dynamic unique node list. Vehicle nodes can promptly select nodes with high reliability from the list of communicable nodes to join their unique node list, while also promptly removing nodes with low reliability from their unique node list. Combining these strategies, we propose DK-PBFT, an improved Practical Byzantine Fault Tolerance consensus algorithm. The algorithm meets the efficiency and mobility requirements of vehicular networks. Through theoretical analysis, ESBCP could prevent external and internal security risks while reducing communication overhead. Experimental verification demonstrated that ESBCP effectively reduces consensus latency and improves transaction throughput. Our proposed ESBCP can be used in other application scenarios that require high consensus efficiency.