The rapid expansion of the UAV sector introduces new use cases, but a heavy reliance on GNSS signals leaves drone fleets vulnerable to jamming and spoofing. To address these vulnerabilities, we introduce a lightweight coordination protocol that ensures secure mission completion during GNSS disruptions. Leveraging inter-drone communication and RSSI-based ranging, the protocol enables relative positioning without dedicated sensors, incurring virtually zero bandwidth or computational overhead. This allows fleets to maintain formation integrity and navigate safely despite degraded or manipulated GNSS data.Validated via extensive NS-3 simulations, the system consistently detects coordinated multi-drone attacks within 500 to 700 milliseconds. Upon detection, the correction algorithm enables targeted drones to recover their trajectories with an average positioning error under 3 meters while successfully averting intra-swarm collisions.
Anti-Spoofing RSSI-Based Defense Protocol for UAV Swarms / Conti, M., Cornacchia, M., Corò, F., Rigoni, G.. - (2026), pp. 1-9. (IEEE Conference on Local Computer Networks Coimbra; Portugal ) [10.1109/lcn67947.2026.11660779].
Anti-Spoofing RSSI-Based Defense Protocol for UAV Swarms
Cornacchia, Matteo;Rigoni, Giulio
2026
Abstract
The rapid expansion of the UAV sector introduces new use cases, but a heavy reliance on GNSS signals leaves drone fleets vulnerable to jamming and spoofing. To address these vulnerabilities, we introduce a lightweight coordination protocol that ensures secure mission completion during GNSS disruptions. Leveraging inter-drone communication and RSSI-based ranging, the protocol enables relative positioning without dedicated sensors, incurring virtually zero bandwidth or computational overhead. This allows fleets to maintain formation integrity and navigate safely despite degraded or manipulated GNSS data.Validated via extensive NS-3 simulations, the system consistently detects coordinated multi-drone attacks within 500 to 700 milliseconds. Upon detection, the correction algorithm enables targeted drones to recover their trajectories with an average positioning error under 3 meters while successfully averting intra-swarm collisions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


