Cooperative ad hoc unmanned aerial vehicle (UAV) networks need essential security services to ensure their communication security. Cryptography, as the inseparable tool for providing security services, requires a robust key management system. Alas, the absence of infrastructure in cooperative networks leads to the infeasibility of providing conventional key management systems. Key pre-distribution schemes have shown promising performance in different cooperative networks due to their lightweight nature. However, intermediate decryption-encryption (DE) steps and the lack of key updates are the most concerning issues they suffer from. In this paper, we propose a simple and effective key management algorithm inspired by the idea of key pre-distribution, where it utilizes the highly dynamic UAV node movement in 3D space to provide the key update feature and optimizes the number of intermediate DE steps. Although it is a general model for any mobile ad hoc network, we have selected UAV network as an example domain to show the efficiency of the model given the high mobility. We define the communication density parameter to analytically show that using any highly dynamic random movement pattern leads our algorithm to work effectively. To show the proposed algorithm's effectiveness, we exhaustively analyze its security and performance in the UAV network using the ns-3 network simulator. Results validate our analytical findings and show how the highly dynamic UAV network movement helps our algorithm to provide the key update feature and to optimize the number of DE steps.

中文翻译：

---

无人机的高动态3D运动如何提高网络安全性？

协作式特设无人机（UAV）网络需要基本的安全服务，以确保其通信安全。密码学作为提供安全服务的不可分割的工具，需要强大的密钥管理系统。遗憾的是，协作网络中缺少基础结构会导致无法提供常规的密钥管理系统。关键的预分配方案由于其轻量性质，在不同的协作网络中已显示出令人鼓舞的性能。但是，中间的解密-加密（DE）步骤和缺少密钥更新是他们最担心的问题。在本文中，我们提出了一种简单有效的密钥管理算法，该算法受密钥预分配的思想启发，它利用3D空间中高度动态的无人机节点移动来提供关键更新功能并优化中间DE步数。尽管它是任何移动自组织网络的通用模型，但我们选择了UAV网络作为示例域，以在高移动性的情况下展示该模型的效率。我们定义通信密度参数以分析性地表明，使用任何高度动态的随机运动模式都可以使我们的算法有效地工作。为了显示该算法的有效性，我们使用ns-3网络模拟器详尽分析了其在无人机网络中的安全性和性能。结果验证了我们的分析结果，并显示了高度动态的无人机网络运动如何帮助我们的算法提供关键更新功能并优化DE步数。