Design and Performance Evaluation of Secure RF and WiFi-Based Communication in Drone Swarms via Testbed Implementation

2026-06-25

AI Summary

This study addresses the vulnerability of unmanned aerial vehicle (UAV) swarms to eavesdropping attacks due to the lack of encryption in the MAVLink protocol. To mitigate this, the authors propose MAVShield, a lightweight cryptographic framework integrating AES-CTR, Speck-CTR, ChaCha20, and Rabbit stream ciphers, and evaluate its performance on a real-world four-UAV flight platform over RF and WiFi channels. The work also introduces an innovative enhancement to the artificial potential field method by computing attractive and repulsive forces directly in the geodetic coordinate system, thereby eliminating trajectory oscillations and local minima caused by coordinate transformations. Experimental results demonstrate that MAVShield achieves near-native communication performance in terms of CPU utilization, memory overhead, and packet delivery ratio, while effectively resisting key-recovery attacks, ensuring telemetry confidentiality, and enabling secure formation control and collision avoidance.

Abstract

Unmanned aerial vehicle (UAV) swarms rely on distributed coordination and cooperative communication to support scalable operations, extended coverage, and applications such as surveillance and real-time data exchange. Wireless technologies such as radio frequency (RF) and WiFi are widely used for UAV-to-UAV and UAV-to-ground control station (GCS) communication but introduce significant security challenges. MAVLink, the predominant communication protocol in UAV systems, provides message integrity and authentication but lacks built-in encryption, leaving telemetry traffic vulnerable to eavesdropping. In our previous work, we proposed MAVShield, a lightweight encryption framework for MAVLink communications. In this paper, MAVShield, AES-CTR, Speck-CTR, ChaCha20, and Rabbit are integrated into four custom-built UAVs to establish secure communication links over RF and WiFi channels. Their performance is evaluated through flight experiments using a UAV swarm testbed. Encrypted telemetry data enable autonomous formation control and collision avoidance during flight. For collision avoidance, we develop a modified artificial potential field (APF) algorithm that computes attractive and repulsive forces directly in geodetic coordinates, eliminating Cartesian transformations and reducing trajectory oscillations while avoiding local-minimum trapping. CPU utilization, memory consumption, and packet delivery ratio (PDR) are measured for each encryption scheme. Results show that MAVShield achieves performance comparable to unencrypted communication while outperforming AES-CTR, Speck-CTR, ChaCha20, and Rabbit in overall efficiency. Algebraic cryptanalysis and Wireshark-based traffic analysis demonstrate resistance to key-recovery attacks and protection of telemetry confidentiality. The results indicate that MAVShield is an efficient and secure solution for UAV swarm communication.

Problem

• UAV swarm
• secure communication
• MAVLink
• encryption
• telemetry confidentiality

Innovation

• MAVShield
• UAV swarm security
• lightweight encryption
• geodetic APF algorithm
• secure telemetry