College of Mathematics and Statistics, Northwest Normal University, Lanzhou, China.
Key Laboratory of Cryptography and Data Analytics, Northwest Normal University, Lanzhou, China.
PLoS One. 2024 Jan 30;19(1):e0297002. doi: 10.1371/journal.pone.0297002. eCollection 2024.
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.
在物联网大数据环境下,智能医疗保健与云计算相结合得到了发展。然而,随着智能医疗保健系统中大量数据的产生和对实时数据处理的需求,传统的云计算不再适用于物联网中资源受限的设备。为了解决这个问题,我们结合雾计算的优势,提出了一种云雾辅助的基于属性的智能医疗保健签名加密方案。在所构建的“云-雾-终端”三层模型中,在患者(数据所有者)签名加密之前,它首先将一些繁重的计算负担卸载到雾节点,并且医生(数据用户)在提供盲私钥进行不解密之前,也将一些复杂的操作外包给雾节点,这大大降低了患者和医生资源受限设备的计算开销,提高了计算效率。从而实现了轻量级签名加密算法。安全性分析表明,如果计算双线性 Diffie-Hellman 问题和判定双线性 Diffie-Hellman 问题成立,所提出的方案在选择密文攻击下可实现不可区分性,在选择消息攻击下可实现存在性不可伪造性。此外,性能分析表明,我们的新方案对医生和患者的计算开销都较小,因此具有更高的计算效率,非常适合智能医疗保健的应用场景。