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

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.