当前位置: X-MOL 学术Electronics › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Robust Cyber-Physical System Enabled Smart Healthcare Unit Using Blockchain Technology
Electronics ( IF 2.9 ) Pub Date : 2022-09-26 , DOI: 10.3390/electronics11193070
Rupa Ch, Gautam Srivastava, Yarajarla Lakshmi Venkata Nagasree, Akshitha Ponugumati, Sitharthan Ramachandran

With the growing demand for smart, secure, and intelligent solutions, Industry 4.0 has emerged as the future of various applications. One of the primary sectors that are becoming more vulnerable to security assaults like ransomware is the healthcare sector. Researchers have proposed various mechanisms in smart and secure health care systems with this vision in mind. Existing systems are vulnerable to security attacks on medical data. It is required to build a real-time diagnosis device using a cyber-physical system with blockchain technology in a considerable manner. The proposed work’s main purpose is to build secure, real-time preservation and tamper-proof control of medical data. In this work, the Bayesian grey filter-based convolution neural network (BGF-CNN) approach is used to enhance accuracy and reduce time complexity and overhead. Additionally, PSO and GWO optimization techniques are used to improve network performance. As an outcome of the proposed work, the privacy preservation of medical data is improved with a high accuracy rate by a blockchain-based cyber-physical system using a deep neural network (BGF Blockchain). To summarize, the proposed system helps in the privacy preservation of medical data along with a reduction in communication overhead using the Bayesian Grey Filter–CNN.

中文翻译:

使用区块链技术支持强大的网络物理系统的智能医疗单元

随着对智能、安全和智能解决方案的需求不断增长,工业 4.0 已成为各种应用的未来。医疗保健行业是越来越容易受到勒索软件等安全攻击的主要行业之一。考虑到这一愿景,研究人员在智能和安全的医疗保健系统中提出了各种机制。现有系统容易受到对医疗数据的安全攻击。需要大量使用区块链技术的信息物理系统构建实时诊断设备。拟议工作的主要目的是建立对医疗数据的安全、实时保存和防篡改控制。在这项工作中,基于贝叶斯灰色滤波器的卷积神经网络 (BGF-CNN) 方法用于提高准确性并降低时间复杂度和开销。此外,PSO 和 GWO 优化技术用于提高网络性能。作为拟议工作的结果,通过使用深度神经网络(BGF 区块链)的基于区块链的网络物理系统以高精度提高了医疗数据的隐私保护。总而言之,所提出的系统有助于保护医疗数据的隐私,同时使用贝叶斯灰色滤波器-CNN 减少通信开销。
更新日期:2022-09-26
down
wechat
bug