A lightweight attribute-based signcryption scheme based on cloud-fog assisted in smart healthcare

• Published in: PloS one 2024-01, Vol.19 (1), p.e0297002
• Main Authors: Sun, Yanzhong, Du, Xiaoni, Niu, Shufen, Zhou, Siwei
• Format: Article
• Language: English
• Subjects: Access control; Algorithms; Analysis; Big Data; Cloud computing; Computer and Information Sciences; Computer applications; Confidentiality; Data processing; Digital signatures; Earth Sciences; Edge computing; Efficiency; Encryption; Engineering and Technology; Fog; Health care; Health care industry; Innovations; Internet of Things; Investment analysis; Lightweight; Medicine and Health Sciences; Nodes; Outsourcing; People and Places; Personal health; Physical Sciences; Physicians; Privacy; Real time; Research and Analysis Methods; Technology application; Weight reduction
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0297002

In the environment of big data of the Internet of Things, smart healthcare is developed in combination with cloud computing. However, with the generation of massive data in smart healthcare systems and the need for real-time data processing, traditional cloud computing is no longer suitable for resources-constrained devices in the Internet of Things. In order to address this issue, we combine the advantages of fog computing and propose a cloud-fog assisted attribute-based signcryption for smart healthcare. In the constructed "cloud-fog-terminal" three-layer model, before the patient (data owner)signcryption, it first offloads some heavy computation burden to fog nodes and the doctor (data user) also outsources some complicated operations to fog nodes before unsigncryption by providing a blinded private key, which greatly reduces the calculation overhead of resource-constrained devices of patient and doctor, improves the calculation efficiency. Thus it implements a lightweight signcryption algorithm. Security analysis confirms that the proposed scheme achieves indistinguishability under chosen ciphertext attack and existential unforgeability under chosen message attack if the computational bilinear Diffie-Hellman problem and the decisional bilinear Diffie-Hellman problem holds. Furthermore, performance analysis demonstrates that our new scheme has less computational overhead for both doctors and patients, so it offers higher computational efficiency and is well-suited for application scenarios of smart healthcare.