为医疗保健和其他高风险数据环境中的AI驱动的网络威胁开发零信任架构:系统性审查
Kanwarjit Zakhmi1, Azhar Ushmani2, Manas Ranjan Mohanty3
1Technical Operations, Amazon Web Services (AWS), Portland, USA.
Cureus
|July 8, 2025
概括
零信任架构 (ZTA) 可以应对医疗保健中的AI网络威胁,但实施面临挑战. 需要更多的现实研究来弥合ZTA理论和实践之间的差距,以实现有效的AI安全.
科学领域:
- 网络安全 网络安全
- 医疗保健中的人工智能 (AI)
- 信息安全框架 信息安全框架
背景情况:
- 在医疗保健中采用人工智能引入了挑战传统安全的先进网络威胁.
- 零信任架构 (ZTA) 为增强安全提供了"永远不要信任,总是验证"的框架.
- 现有的安全模型与复杂的AI驱动的网络攻击作斗争.
研究的目的:
- 系统地审查ZTA的实施,以减轻医疗保健中的AI驱动的网络威胁.
- 为了确定ZTA理论原则和现实世界的应用之间的差距.
- 分析ZTA在人工智能安全部署中的挑战和伦理考虑.
主要方法:
- 按照PRISMA 2020指南进行系统审查.
- 搜索了五个主要数据库的相关研究,包括15项选定的研究.
- 使用混合方法评估工具 (MMAT) 评估方法质量.
主要成果:
- ZTA原则适用于AI威胁,特别是可解释AI (XAI) 和持续监控.
- 在ZTA标准化,经验验验证和利益相关者信任方面存在重大差距.
- 主要挑战包括缺乏有效度指标,道德/监管障碍 (偏见,隐私) 和运营障碍 (互操作性,阻力).
结论:
- 存在着一个关键的研究与实践的分歧,只有4/15项研究显示了现实世界的ZTA证据.
- 由于理论重点和实施困难,ZTA的潜力未得到充分利用.
- 迫切需要跨学科合作,标准化框架和试点研究,以推进适应性,基于证据的医疗保健ZTA模型.
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