GDM-DTM:一个集团决策支持的动态信任管理方法,用于在低空无人机网络中检测恶意节点
Yabao Hu1, Yulong Gan1, Haoyu Wu1
1College of Artificial Intelligence, Tianjin University of Science and Technology, Tianjin 300457, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
本研究介绍了一种支持集团决策 (GDM) 的动态信任管理 (DTM) 方法,用于无人机网络. 通过有效检测没有地面基础设施的恶意无人机,GDM-DTM提高了安全性.
科学领域:
- 网络安全 网络安全
- 网络安全 网络安全
- 航空航天工程 航空航天工程
背景情况:
- 无人机网络对于低空经济至关重要,但面临着诸如节点透和数据改等重大安全威胁.
- 目前的信任管理方案受到基础设施依赖,不充分的多维信任评估和对勾结攻击的易感性限制.
研究的目的:
- 为低空无人机网络提出一种新的集团决策 (GDM) 支持的动态信任管理 (DTM) 方法.
- 提高无人机网络对恶意活动的安全性和可靠性.
主要方法:
- 拟议的GDM-DTM方法包含四个核心组件:主观一致性评估,客观一致性评估,全球一致性评估和自我证明一致性评估.
- 集成了一个具有多属性的信任计算的动态信任调整机制,用于基础设施独立的信任评估和恶意无人机检测.
主要成果:
- GDM-DTM实现了85.04%的准确性和91.66%的F-score,恶意节点比率为30%.
- 这比现有的最先进的方法有了显著的改进,精度增加了6.04%,F-score增加了3.71%.
结论:
- 该GDM-DTM方法为低空无人机网络的信任管理提供了有效和强大的解决方案.
- 拟议的方法提高了恶意无人机检测能力,同时减少了对地面基础设施的依赖.
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