Secure transfer of robust healthcare data using blockchain-based privacy

被引:4
|
作者
Kumar, Maddila Suresh [1 ]
Nagalakshmi, Vadlamani [1 ]
机构
[1] GITAM Deemed Univ, Dept Comp Sci, GITAM Sch Sci, Visakhapatnam 530045, Andhra Pradesh, India
关键词
Blockchain-based Privacy-Preserving and Robust Healthcare data (BPPRH); Modified Fuzzy Particle Swarm Optimization (MFPSO); Hypervisor; Virtual machines (VMs); Edge-Cloud based Collaborative Systems (ECCS); Healthcare data; Cloud computing;
D O I
10.1007/s10586-023-04011-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The healthcare sector is continuously evolving, and it is anticipated that the next healthcare model would be information-focused. Cloud computing technology can help the sector handle heterogeneous sources of data and the effective convergence of data. Due to security and privacy considerations, it is challenging to transfer a medical record from multiple hospital databases. Consequently, the article proposed a blockchain-based patient information management system by using the Blockchain-based Privacy-Preserving and Robust Healthcare data (BPPRH). This transfers the medical data to the patient through the cloud more securely. The cloud is modelled with the hypervisor and VMs. During the data transmission or storage in the cloud, there are several attacks like ransomware, malicious insiders, Man-in-the-middle attack, malware injection attacks, and Denial-of-Service attacks (DoS) occur in the network. Modified Fuzzy Particle Swarm Optimization (MFPSO) is presented to detect these threats. After detecting the attacks, Edge-Cloud-based Collaborative Systems (ECCS) prevent the data from attackers with the use of Regularized Maximum Likelihood Estimation, Inverse Network, and Shadow Model Reconstruction models. The results showed that the system provides better security with high accuracy of 99.32% respectively. The proposed Blockchain-based architecture is designed to contribute to the healthcare management systems' robustness and to avoid recorded security limitations in commonly used systems for smart healthcare respectively.
引用
收藏
页码:1275 / 1291
页数:17
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