智能医疗保健系统的安全分析
Mariam Ibrahim1, Abdallah Al-Wadi1, Ruba Elhafiz1
1Department of Mechatronics Engineering, German Jordanian University, Amman 11180, Jordan.
Sensors (Basel, Switzerland)
|June 19, 2024
概括
一个新的入侵检测系统 (IDS) 通过使用 honeypot 和整体模型来增强医疗物联网 (IoMT) 的安全性. 这个强大的系统有效地检测和分类对IoMT网络的网络攻击,保护敏感的患者数据.
科学领域:
- 网络安全 网络安全
- 医疗信息学 医疗信息学
- 网络安全 网络安全
背景情况:
- 医疗事物互联网 (IoMT) 在医疗保健中的整合使得有效的数据分析能够改善患者诊断.
- 然而,IoMT网络面临着重大安全风险,包括数据泄露和网络流量拦截,危及患者的机密性.
- 现有的安全措施不足以应对IoMT环境中不断变化的威胁格局.
研究的目的:
- 开发和评估专门为医疗物联网 (IoMT) 网络设计的强大的入侵检测系统 (IDS).
- 加强在IoMT生态系统中传输的敏感患者数据的安全性和隐私性.
- 提高检测针对IoMT基础设施的各种网络攻击的准确性和可靠性.
主要方法:
- 实施了一种新型的IDS,其中包含一个蜂,以诱骗攻击者并减少攻击表面.
- 利用整体机器学习方法,结合物流回归和K-近邻算法,以增强检测能力.
- 使用两种不同的IoMT数据集进行性能评估,其中包括各种攻击类型,包括Man-In-The-Middle (MITM),数据注入和分布式拒绝服务 (DDOS).
主要成果:
- 拟议的整体IDS在识别和分类IoMT网络中的恶意活动方面表现出高效.
- 在第一个数据集上达到92.5%的高准确率,在第二个数据集上达到99.54%.
- 第一个数据集的精度为96.74%,第二个数据集的精度为99.228%,表明可靠的攻击检测.
结论:
- 开发的IDS利用 honeypot 和ensemble模型,为保护IoMT网络提供了强大的解决方案.
- 整体方法显著提高了医疗保健环境中入侵检测的准确性和精度.
- 这项研究有助于保护敏感的患者数据,并确保对复杂的网络威胁的IoMT系统的完整性.
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