Robotic systems are currently deployed in sectors ranging from industrial manufacturing to healthcare to agriculture, adding benefits in production times, patient outcomes, and yields. This trend towards greater automation and human robot collaborative work environments, while providing great opportunities, also highlights a critical gap in cybersecurity research. These systems rely on network communication to coordinate movement, meaning that security breaches could result in the robot acting in ways that may endanger people and property.
Current cybersecurity approaches have been shown to be insufficient in blocking sophisticated attacks aimed at networked robotic motion-control systems.
To address this gap, Jun Ueda, Professor and ASME Fellow in the George W. Woodruff School of Mechanical Engineering at Georgia Tech, has been awarded ~$700,000.00 by the National Science Foundation to establish methods to enhance cybersecurity for networked motion-control system. The research will focus on the unique geometric vulnerabilities in networked robotic systems and stealthy false data injection attacks that exploit geometric coordinate transformations to maintain mathematical consistency in robotic dynamics while altering physical world behavior.
Unsing an interdisciplinary approach that will combine research methodology from system dynamics, control, communication, differential geometry and cybersecurity engineering, Ueda hopes to establish new mathematical tools for analyzing robotic security and develop safer networked robotic systems that successfully repel system intrusion, manipulation attacks, and attacks that mislead operators.
This article refers to NSF Program Foundational Research in Robotics (FRR) Award # 2112793
A Geometric Approach for Generalized Encrypted Control of Networked Dynamical Systems