移动患者身份验证的新型密钥分配灵感来自联合学习概念,基于迪菲-赫尔曼圆曲线
Orieb AbuAlghanam1, Hadeel Alazzam2, Wesam Almobaideen1,3
1Department of Computer Science, The University of Jordan, Amman 77110, Jordan.
Sensors (Basel, Switzerland)
|April 26, 2025
概括
这项研究介绍了一种新的受联邦学习 (FL) 启发的系统,用于安全的电子医疗通信. 它使移动患者在不同医疗保健中心的有效密钥分配和身份验证成为可能,减少了存储需求.
科学领域:
- 电子医疗安全 电子医疗安全
- 移动计算 移动计算
- 密码学 密码学 密码学 密码学
背景情况:
- 电子医疗保健中的移动患者需要跨设施的安全通信和无身份验证.
- 现有的密钥分发机制面临的挑战是移动用户的可扩展性和存储开销.
- 联合学习 (FL) 提供了一种分散的方法,可以适应安全的参数共享.
研究的目的:
- 在电子医疗保健中引入用于移动患者身份验证的新型层次密钥分发架构.
- 为了有效和安全的钥匙管理,利用联合学习原则.
- 为了减少移动患者的存储和计算负担.
主要方法:
- 一个由联合学习 (FL) 启发的层次式密钥分配架构.
- 一个中央机构与下属单位共享全球安全参数.
- 当地参数被结合起来,生成并向移动患者分发对称的密钥.
- 使用SPAN-AVISPA和BAN逻辑进行协议分析的正式安全验证.
主要成果:
- 拟议的FL灵感系统使患者能够存储一个单一的钥匙,最大限度地减少存储开销.
- 正式验证证实了系统的安全性和身份验证能力.
- 性能分析显示,与传统方法相比,计算负载减少,信息交换减少.
- 在动态医疗环境中提高可扩展性和效率.
结论:
- 这种新的架构为移动电子医疗保健提供了一个轻量级,可扩展和安全的密钥分发框架.
- 这种方法有效地解决了在跨设施场景中对稳健的患者身份验证的关键需求.
- 灵感来自FL的方法显著提高了效率,并减少了移动患者的资源需求.
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