Passive User Authentication Utilizing Screen-Touch Trajectory for Unmanned Aerial Vehicle Systems

Jiasheng He

¹School of Computer and Information Engineering, Chuzhou University, Chuzhou, Anhui, 239000, China

²School of Intelligent Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, China

³School of Basic Medicine, Shandong Second Medical University, Weifang, Shandong, 261053, China

*Corresponding author

User identity verification is of great significance for the secure operation of UAV systems. This article exploits the spatial-temporal features of user screen-touch trajectory (STT) to develop a passive user authentication framework for unmanned aerial vehicle (UAV) systems. We first design a multi-dimensional STT data structure to accurately record continuous touch interactions and extract 21 discriminative spatial-temporal features for behavioral characterization. We then construct a classifier based on Random Forest (RF) for robust nonlinear feature learning and also a classifier based on Radial Basis Function Neural Network (RBFNN) for modeling fine-grained touch behavior patterns. By combining the two classifiers and assigning each classifier an appropriate weight, we develop a fusion-based passive user authentication framework. The new framework has the potential to significantly enhance the security of UAV operation systems by offering a flexible, continuous, and non-intrusive authentication solution, and it also can serve as a complementary security layer or an enhancement to traditional authentication mechanisms in UAV ground control systems.

Unmanned Aerial Vehicle Security, Passive Authentication, Screen-touch Trajectory, Spatial-temporal Features, Machine Learning

Guozhu Zhao, Jiasheng He, Yaxin Wang, Zixian Du, Xiaolan Liu, Chenxi Yang, Yichen Li, and Renzhi Ji (2025). Passive User Authentication Utilizing Screen-Touch Trajectory for Unmanned Aerial Vehicle Systems. Journal of Networking and Network Applications, Volume 5, Issue 4, pp. 165–175. https://doi.org/10.33969/J-NaNA.2025.050403.

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