SyncGait Demonstrates 99.84% Accuracy for Long-Range Drone Authentication Using Implicit Gait

Global: SyncGait Enables Long-Distance Drone Authentication via Implicit Gait

Researchers led by Zijian Ling announced a new mutual authentication system for drone delivery on December 29, 2025, that leverages a user’s natural arm swing while walking toward a delivery drone. The system, named SyncGait, aims to verify both the user and the drone at distances exceeding 18 meters without requiring additional hardware or explicit authentication actions.

Background

Unmanned aerial vehicles (UAVs) are increasingly employed for package transport, but their high cost and the value of carried goods create a need for secure, distance‑based authentication to prevent unauthorized access. Existing schemes often rely on short‑range signals or specialized devices, limiting their practicality in real‑world logistics.

Method Overview

SyncGait captures the unique gait pattern generated by a user’s arm swing using the drone’s onboard sensors. By analyzing the implicit motion signature, the system establishes a bidirectional trust relationship between the user and the UAV. The approach does not depend on wearables or explicit gestures, making it transparent to the user.

Experimental Evaluation

The authors collected 14 datasets from 31 participants, covering a variety of walking speeds, clothing, and environmental conditions. Each dataset included recordings at multiple distances, with the longest range surpassing 18 meters. The experiments also incorporated several spoofing scenarios, such as replay attacks and synthetic gait generation.

Performance Results

Across all test conditions, SyncGait achieved an average authentication accuracy of 99.84% at distances greater than 18 m. The system maintained high resilience against the evaluated spoofing attacks, indicating strong robustness for practical deployment.

Implications and Future Directions

The findings suggest that implicit biometric cues can provide reliable, long‑range authentication for UAV delivery services, potentially reducing the need for additional security hardware. The authors note that further research is required to assess performance in densely populated urban settings and to explore integration with existing drone communication protocols.

This report is based on information from arXiv, licensed under See original source. Source attribution required.