Secure connectivity analysis in unmanned aerial vehicle networks

Xin YUAN; Zhi-yong FENG; Wen-jun XU; Zhi-qing WEI; Ren-ping LIU

doi:10.1631/FITEE.1700032

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Secure connectivity analysis in unmanned aerial vehicle networks

Special Feature on 5G Wireless Communication Systems and Technologies | Updated：2022-05-19

- Secure connectivity analysis in unmanned aerial vehicle networks
- 无人机网络中的安全连通性分析
- Frontiers of Information Technology & Electronic Engineering Vol. 19, Issue 3, Pages: 409-422(2018)
- Affiliations：
  
  MOE Key Laboratory of Universal Wireless Communications, Beijing 100876, China
  Global Big Data Technologies Centre, University of Technology Sydney, Sydney NSW2007, Australia
- Author bio：
  
  [ "Xin YUAN, E-mail:yuanxin@bupt.edu.cn" ]
  Zhi-yong FENG, E-mail:fengzy@bupt.edu.cn
  [ "Wen-jun XU, E-mail:wjxu@bupt.edu.cn" ]
  [ "Zhi-qing WEI, E-mail:weizhiqing@bupt.edu.cn" ]
  [ "Ren-ping LIU, E-mail:RenPing.Liu@uts.edu.au" ]
- Funds：
- DOI：10.1631/FITEE.1700032
  CLC： TN92
- Received：10 January 2017，
  
  Revised：2018-;3-15，
  
  Published：2018-03
- Accepted：
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Xin YUAN, Zhi-yong FENG, Wen-jun XU, et al. Secure connectivity analysis in unmanned aerial vehicle networks[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(3): 409-422.
DOI：

Xin YUAN, Zhi-yong FENG, Wen-jun XU, et al. Secure connectivity analysis in unmanned aerial vehicle networks[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(3): 409-422. DOI： 10.1631/FITEE.1700032.

摘要

无人机网络的独特特征包括高动态网络拓扑、高移动性以及野外无线环境可能使得无人机网络容易受到攻击和威胁。本文基于无人机行为、运动模式和无人机之间的信道特征，为无人机网络提出一种新颖的信任模型。该信任模型由直接信任、间接信任、信任集成和信任更新4部分组成。基于信任模型，提出一种无人机网络中安全链路的概念，该概念仅在两个无人机之间既有物理链路又有信任链路时存在。此外，利用两架无人机之间的物理连通概率和安全连通概率，分析无人机网络的连通性。通过随机几何方法，推导得到考虑和不考虑多普勒频偏情况下的物理连通概率和安全连通概率的解析表达式。仿真结果表明，与具有和不具有恶意攻击的物理连接概率相比，提出的信任模型可以保证无人机之间的安全通信和可靠连接，并在无人机网络面临恶意攻击和其他安全隐患时提高网络性能。

Abstract

The distinctive characteristics of unmanned aerial vehicle networks (UAVNs)

including highly dynamic network topology

high mobility

and open-air wireless environments

may make UAVNs vulnerable to attacks and threats. In this study

we propose a novel trust model for UAVNs that is based on the behavior and mobility pattern of UAV nodes and the characteristics of inter-UAV channels. The proposed trust model consists of four parts: direct trust section

indirect trust section

integrated trust section

and trust update section. Based on the trust model

the concept of a secure link in UAVNs is formulated that exists only when there is both a physical link and a trust link between two UAVs. Moreover

the metrics of both the physical connectivity probability and the secure connectivity probability between two UAVs are adopted to analyze the connectivity of UAVNs. We derive accurate and analytical expressions of both the physical connectivity probability and the secure connectivity probability using stochastic geometry with or without Doppler shift. Extensive simulations show that compared with the physical connection probability with or without malicious attacks

the proposed trust model can guarantee secure communication and reliable connectivity between UAVs and enhance network performance when UAVNs face malicious attacks and other security risks.

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references

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