一个全面的安全系统,使医疗保健5.0使用联合学习,入侵检测和区块链实现
Jameel Almalki1, Saeed M Alshahrani2, Nayyar Ahmed Khan2
1Department of Computer Science, College of Computer in Al-Lith, Umm Al-Qura University, Makkah, Makkah, Saudi Arabia.
PeerJ. Computer science
|January 23, 2024
概括
本研究介绍了使用区块链和联合学习的安全医疗监控系统. 这种创新方法提高了疾病分析的准确性和对医疗物联网 (IoMT) 数据的入侵检测.
科学领域:
- 医疗信息学 医疗信息学
- 网络安全 网络安全
- 人工智能的人工智能
背景情况:
- 越来越多的医疗物联网 (IoMT) 设备的采用带来了重大的安全挑战.
- 保护敏感的患者数据和确保IoMT系统的完整性是现代医疗保健中的关键问题.
研究的目的:
- 研究区块链技术与联合学习的整合,以提高医疗保健中的安全性和数据分析.
- 开发一个强大的模型来检测和防止IoMT网络中的恶意活动.
主要方法:
- 实施使用区块链和入侵检测管理 (IDM) 进行IoMT安全的集体方法.
- 利用集中式学习和机器学习算法从集中式数据中进行疾病诊断和治疗建议.
主要成果:
- 通过拟议的联合学习模型,在疾病分析和成检测方面获得了93.89%的准确性.
- 在入侵检测方面表现出97.13%的成功率,确保医疗保健数据的安全性.
结论:
- 联合学习和区块链的结合为安全和准确的医疗监测提供了强大的解决方案.
- 拟议的模型有效地解决了与IoMT设备和数据相关的安全风险,改善了诊断能力.
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