| Literature DB >> 35957478 |
Ajitesh Kumar1, Akhilesh Kumar Singh1, Ijaz Ahmad2, Pradeep Kumar Singh1, Pawan Kumar Verma3, Khalid A Alissa4, Mohit Bajaj5,6, Ateeq Ur Rehman7, Elsayed Tag-Eldin8.
Abstract
Nowadays, in a world full of uncertainties and the threat of digital and cyber-attacks, blockchain technology is one of the major critical developments playing a vital role in the creative professional world. Along with energy, finance, governance, etc., the healthcare sector is one of the most prominent areas where blockchain technology is being used. We all are aware that data constitute our wealth and our currency; vulnerability and security become even more significant and a vital point of concern for healthcare. Recent cyberattacks have raised the questions of planning, requirement, and implementation to develop more cyber-secure models. This paper is based on a blockchain that classifies network participants into clusters and preserves a single copy of the blockchain for every cluster. The paper introduces a novel blockchain mechanism for secure healthcare sector data management, which reduces the communicational and computational overhead costs compared to the existing bitcoin network and the lightweight blockchain architecture. The paper also discusses how the proposed design can be utilized to address the recognized threats. The experimental results show that, as the number of nodes rises, the suggested architecture speeds up ledger updates by 63% and reduces network traffic by 10 times.Entities:
Keywords: blockchain; cyber security; cyberattack; healthcare
Mesh:
Year: 2022 PMID: 35957478 PMCID: PMC9371396 DOI: 10.3390/s22155921
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.847
Figure 1Blockchain in its simplest form.
Figure 2Investment of healthcare industries in the blockchain [2,3].
Figure 3Blockchain awareness among e-healthcare persons [4,5].
Figure 4Challenges and barriers in the adoption of blockchain technology [6,7,8].
Contributions of various researchers in the healthcare sector using the blockchain.
| Application Area | Summary of Work Carried Out or Proposed |
|---|---|
| Ekblaw, A. et al. [ | |
| Xia, Q. et al. [ | |
| Zhang P et al. [ | |
| Fan, K. et al. [ | |
| Jiang, S. et al. [ | |
| Dagher, G.G. et al. [ | |
| Remote patient monitoring (RPM) | Ichikawa, D. et al. [ |
| Griggs, K.N. et al. [ | |
| Pharmaceutical supply chain (PSC) | Bocek, T. et al. [ |
| Bocek, T. et al. [ | |
| Miler et al. [ | |
| Health insurance claims (HIC) | Zaman et al. [ |
Figure 5(a) Data Flow Diagram of the Proposed Approach. (b) The proposed secure architecture for blockchain-based healthcare data management.
Experimental setup.
| Hardware Setup | Processor | Intel Xeon X5355 2.66 GHz (8 Cores) |
| Memory | 8 GB RAM | |
| Storage | 2 × 146 GM | |
| Network Interface | 1 GbE | |
| Software Setup | Anaconda (Spyder) | IDE Used for Implementation |
| Flask | A web framework for blockchain communication | |
| Postman | Display the information | |
| Simulation Criteria | Block Size | 1 MB |
| Hash Function Size | 256 bytes | |
| Nodes (Blockchain cluster) | 100(10), 200(20), 300(30), and 400(40) |
Figure 6The count of blocks grows larger against the aggregate of data moved via bitcoin, LW blockchain, and our proposed secure blockchain architecture.
Figure 7Total processing time and restoring time of blocks against the increase in the number of nodes.
Figure 8Security accuracy analysis when the number of medical records increases.
Figure 9Privacy accuracy analysis when the number of medical records increases.
Figure 10Analysis of transaction throughput.
Figure 11The simulated outcomes according to the bandwidth and number of iterations.
Figure 12According to the execution time and number of medical records, the simulated outcomes.