Work

Security authentication and 3D tracking of unmanned autonomous vehicles with optical ID tags

Year: 2026

Type: article

Abstract: Unmanned Autonomous Vehicles (UAVs) are increasingly deployed across various applications, necessitating techniques for secure tracking and authentication against spoofing vulnerabilities. While physically unclonable function (PUF)-based optical ID tags offer secure signatures, conventional speckle acquisition systems struggle to extract full three-dimensional (3D) spatial coordinates of UAVs due to poor speckle sensitivity to longitudinal movements of UAVs. To overcome this problem, we propose a hybrid dual-path optical acquisition system by supplementing a security authentication system with a 3D integral imaging sensing system. This modification introduces two challenges: 1) data of mixed modality, which are both 2D and 3D videos, and 2) the possibility of the optical encryption key information leaking into the parameters of the processing pipeline. We propose a two-step framework where a 3D U-Net extracts 3D spatial priors before a separate spatio-temporal fusion network integrates these 3D spatial priors with the encrypted speckle signatures to infer temporal dynamics. The proposed separation of networks is designed to reduce the potential leakage of the optical key into the network weights by preventing the unencrypted speckle data from being jointly processed with the encrypted speckle patterns. Experimental validations performed in the lab demonstrate that our spatio-temporal integrated network maintains the 75 th percentile of the Euclidean tracking error below 1.1 voxels for precise 3D spatial localization and achieves a high F1-score across all test scenarios. The results confirm that the proposed framework has the potential to accomplish simultaneous 3D tracking and security authentication of UAVs, offering a spoofing-resistant solution based on physical optical encryption for advanced surveillance, defense, and autonomous navigation applications.

Source: Optics Express

DOI: 10.1364/oe.614496

Authors: Jiheon Lee, Saurabh Goswami, Bahram Javidi

Language: English

Topic: Physical Unclonable Functions (PUFs) and Hardware Security

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,270

Funder: Air Force Office of Scientific Research