相关实验视频

联合增强学习驱动的多任务优化,以实现强大而道德的边缘物联网安全

Yi Li1, Haitao Wang2, Guoming Xu3

  • 1School of Mechanical and Electrical Engineering, Quanzhou University of Information Engineering, Quanzhou, 362000, China. liyi2025@qzuie.edu.cn.

Scientific reports
|January 16, 2026
PubMed
概括

这项研究介绍了一个联邦强化学习 (FRL) 框架,用于边缘物联网 (IoT) 校园安全. 该系统平衡了检测准确性,效率和隐私,优于传统方法.

关键词:
敌对的强度 敌对的强度校园网络安全 校园网络安全边缘物联网 边缘物联网联合强化学习学习的联合强化学习量化意识培训的培训

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