基于综合信任约束的Q-learning无人机自组网安全路由协议

柳亚男; 树赟; 张正; 邱硕; 沈计鹏; 王鹏飞; 仓基云

doi:10.11959/j.issn.1000-0801.DXKX260235

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基于综合信任约束的Q-learning无人机自组网安全路由协议

专题:低空智联网 | 更新时间：2026-06-23

- 基于综合信任约束的Q-learning无人机自组网安全路由协议
- Q-learning-based secure routing protocol for uav ad hoc networks constrained by comprehensive trust
- 电信科学 2026年
- 作者机构：
  
  1.金陵科技学院网络安全学院，江苏南京 211169
  2.河南通达电缆股份有限公司，河南洛阳 471999
  3.东南大学网络空间安全学院，江苏南京 211189
- 作者简介：
  
  柳亚男（1984− ），女，江苏南京人，博士，金陵科技学院副教授，主要研究方向为密码协议，物联网安全。
  树赟（2001− ），男，江苏南京人，主要研究方向为：物联网，网络安全。
- 基金信息：
  
  国家自然科学基金项目(61902163);江苏高校“青蓝工程”项目;河南省博士后科研项目
- DOI：10.11959/j.issn.1000-0801.DXKX260235
  中图分类号： TP393
- 收稿：2026-04-16，
  
  修回：2026-05-31，
  
  录用：2026-06-23，
- 稿件说明：
移动端阅览
柳亚男, 树赟, 张正, 等. 基于综合信任约束的Q-learning无人机自组网安全路由协议[J/OL]. 电信科学, 2026.

LIU Yanan, SHU Yun, ZHANG Zheng, et al. Q-learning-based secure routing protocol for uav ad hoc networks constrained by comprehensive trust[J/OL]. Telecommunications Science, 2026.
柳亚男, 树赟, 张正, 等. 基于综合信任约束的Q-learning无人机自组网安全路由协议[J/OL]. 电信科学, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260235.

LIU Yanan, SHU Yun, ZHANG Zheng, et al. Q-learning-based secure routing protocol for uav ad hoc networks constrained by comprehensive trust[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260235.

摘要

针对无人机自组网中自私节点易进入转发路径，进而导致传输可靠性下降的问题，提出了基于综合信任约束的Q-learning安全路由协议。该协议面向多跳数据汇聚场景，利用直接信任、间接信任、能量信任和负载信任构建综合信任模型，并采用CRITIC权重法实现动态赋权。在此基础上，节点根据综合信任值形成可信候选邻居集合，再结合Q-learning实现逐跳路由决策。仿真结果表明，该协议能够有效减少自私节点对路由过程的干扰，提高分组投递率，降低端到端时延。说明该协议能够为高动态无人机自组网中的安全稳定传输提供有效支持。

Abstract

To address the problem that selfish nodes in unmanned aerial vehicle ad hoc networks could easily enter forwarding paths

thereby degrading transmission reliability

a Q-learning-based secure routing protocol with comprehensive trust constraints was proposed. For multi-hop data aggregation scenarios

a comprehensive trust model was constructed by integrating direct trust

indirect trust

energy trust

and load trust

and dynamic weighting was achieved by using the CRITIC weighting method. On this basis

a trusted candidate neighbor set was formed according to the comprehensive trust value

and hop-by-hop routing decisions were made in combination with Q-learning. Simulation results showed that the proposed protocol effectively reduced the interference of selfish nodes with the routing process

improved packet delivery ratio

and decreased end-to-end delay. The protocol is effective in supporting secure and reliable transmission in highly dynamic unmanned aerial vehicle ad hoc networks.

关键词

Keywords

references

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