一个联合的边缘情报框架,具有基于信任的访问控制,用于安全和保护隐私的物联网系统
1Department of Information Technology, A. V. C. College of Engineering, Mannampandal, Mayiladuthurai, Tamil Nadu, 609305, India. vvpadhuavc@gmail.com.
Scientific reports
|October 14, 2025
概括
AI-SET框架通过在网络边缘使用人工智能 (AI) 增强物联网 (IoT) 安全性. 它改善了入侵检测和访问控制,同时保护了弹性物联网系统的数据隐私.
科学领域:
- 网络安全 网络安全
- 人工智能的人工智能
- 物联网的物联网,就是物联网.
背景情况:
- 物联网生态系统的快速增长带来了重大的安全和隐私挑战.
- 传统的以云为中心的安全模型由于带宽,延迟和信任要求,对物联网不够.
- 边缘计算提供了一个去中心化的方法来解决物联网安全局限性.
研究的目的:
- 为增强物联网安全提出人工智能驱动的安全边缘信任框架 (AI-SET).
- 整合网络入侵检测与联邦学习,以实现基于信任的自适应性访问控制.
- 为物联网系统提供弹性和保护隐私的安全解决方案.
主要方法:
- 实现了边缘居民入侵检测系统 (IDS) 与轻量级AI算法进行实时异常检测.
- 使用修改后的FedAvg算法来保护隐私的联合学习,结合差异隐私和同态加密.
- 开发了一个动态访问控制系统,使用信任评估模型进行实时设备权限评估.
主要成果:
- 与标准方法相比,AI-SET在入侵检测方面显示出更高的准确性和更好的通信性能.
- 该框架实现了卓越的访问控制安全性,证明了对模型中毒和系统漏洞的免疫力.
- AI-SET保持了低的运营成本,并在整个运营过程中确保了安全的数据隐私.
结论:
- 对于未来的物联网部署,AI-SET提供了一个可适应,弹性和隐私意识的安全框架.
- 该框架有效地结合了边缘智能,安全网络操作和自动化信任管理.
- 基于边缘的AI和联合学习对于解决复杂的物联网安全挑战至关重要.
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