The unmanned aerial vehicle (UAV) network plays important roles in emergency communications. However, it is challenging to design reliable routing strategies that ensure low latency, energy efficiency, and security in the dynamic and attack-prone environments. To this end, we design a secure routing architecture integrating software-defined networking (SDN) for centralized control and blockchain for tamper-proof trust management. In particular, a novel security degree metric is introduced to quantify the UAV trustworthiness. Based on this architecture, we propose a beam search-proximal policy optimization (BSPPO) algorithm, where beam search (BS) pre-screens the high-security candidate paths, and proximal policy optimization (PPO) performs hop-by-hop routing decisions to support dynamic rerouting upon attack detections. Finally, extensive simulations under varying attack densities, packet sizes, and rerouting events demonstrate that BSPPO outperforms PPO, BS-Q learning, and BS-actor critic in terms of delay, energy consumption, and transmission success rate, showing the outstanding robustness and adaptability.

翻译：无人机网络在应急通信中扮演着重要角色。然而，在动态且易受攻击的环境中，设计能够确保低延迟、高能效与安全性的可靠路由策略极具挑战。为此，我们设计了一种集成软件定义网络（SDN）与区块链的安全路由架构，其中SDN提供集中控制，区块链则实现防篡改的信任管理。特别地，本文引入了一种新颖的安全度指标以量化无人机的可信度。基于该架构，我们提出了一种波束搜索-近端策略优化（BSPPO）算法，其中波束搜索（BS）预先筛选高安全性的候选路径，而近端策略优化（PPO）则执行逐跳路由决策，以支持在检测到攻击时进行动态重路由。最后，在不同攻击密度、数据包大小和重路由事件下的大量仿真实验表明，BSPPO在延迟、能耗和传输成功率方面均优于PPO、BS-Q学习和BS-actor critic算法，展现出卓越的鲁棒性和适应性。