区块链框架与物联网设备,使用联合学习来实现可持续的医疗保健系统
B Bhasker1, P Muralidhara Rao2, P Saraswathi3
1School of Computing and Information Technology, REVA University, Bangalore, Karnataka, 560064, India.
Scientific reports
|July 23, 2025
概括
本研究介绍了可持续医疗保健系统 (FBCI-SHS) 的联合区块链-IoT框架,以增强智能医疗保健. 该系统确保数据隐私,并改善疾病和入侵检测,以积极监控患者.
科学领域:
- 聪明的医疗保健 智能医疗保健
- 医疗事物的互联网 (IoMT)
- 医疗保健 5.0 在线
背景情况:
- 安全和隐私在快速发展的医疗物联网 (IoMT) 中至关重要.
- 机器学习 (ML) 和区块链 (BC) 增强了医疗保健5.0,创造了智能医疗保健.
- 机器学习的集中数据存储库引发了隐私和监管方面的担忧.
研究的目的:
- 为可持续医疗保健系统 (FBCI-SHS) 提出一个联合区块链-IoT框架.
- 使用联合学习 (FL) 和区块链开发安全的健康监测系统.
- 实施入侵检测系统 (IDS) 以加强医疗保健网络安全.
主要方法:
- 联合学习 (FL) 允许分布式模型训练,同时保持本地数据控制.
- 区块链技术提高了医疗保健系统的安全性,隐私性和互操作性.
- 侵入检测系统 (IDS) 监控网络流量以发现潜在的威胁.
主要成果:
- 在FBCI-SHS的数据隐私和安全方面,FBCI-SHS的数据隐私和安全率达到98.73%.
- 侵入者检测效率达到97.16%,疾病检测准确率为96.425%.
- 积极的医疗保健管理改善了98.37%,具有96.74%的互操作性.
结论:
- 拟议的FBCI-SHS非常适合安全的医疗监测和积极的医疗保健.
- 该系统通过联合学习有效地解决了隐私问题.
- ML,BC和IoMT的整合为智能医疗保健系统提供了重大进步.
关键词:
区块链 区块链 区块链 区块链联合学习是联合学习.物联网 (IoT) 的物联网 (IoT) 的物联网.入侵检测系统的入侵检测系统监控系统监控系统智能医疗保健是一个智能医疗保健.可持续的医疗保健系统更多相关视频
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