Time-varying parameter affine transformation-based perfectly undertectable attack (TV-ATPA) paper published in Control Engineering Practice

Kwon, Hyuk Bin, Meriem Ernez, and Jun Ueda. “Time-Varying Affine Transformation-based Perfectly Undetectable Attacks: Eliminating Timing Constraints and Enabling Destination Control” Control Engineering Practice, Vol. 175, October 2026 Abstract This paper presents a theoretical framework for Time-Varying Affine Transformation-based Perfectly Undetectable Attacks (TV-ATPA) on linear time-invariant (LTI) control systems. The…

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Mathworks Academic Course Support (Gift)

A $15,000 MathWorks Academic Course Support award (gift) has been awarded for the project “Developing a MATLAB Library for Secure Control and Cyber‑Physical Systems Resilience Education.” The support will enable the development of MATLAB‑based educational tools that enhance hands‑on learning in secure control and cyber‑physical systems, strengthening curriculum and student…

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Paper on perfectly undetectable attack on mobile robot dynamics and attack detection using state monitoring function published in Transactions on Robotics

Perfectly Undetectable Reflection and Scaling False Data Injection Attacks via Affine Transformation on Mobile Robot Trajectory Tracking Control, 10.1109/TRO.2025.3626620, IEEE Transactions on Robotics, https://ieeexplore.ieee.org/document/11219216Jun Ueda and Hyukbin Kwon With the increasing integration of cyber-physical systems (CPS) into critical applications, ensuring their resilience against cyberattacks is paramount. A particularly concerning threat…

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Paper on Affine Transformation-based Perfectly Undetectable False Data Injection Attacks published in IEEE Trans. Industrial Cyber-Physical Systems

https://ieeexplore.ieee.org/document/11183579 J. Ueda, “Affine Transformation-based Perfectly Undetectable False Data Injection Attacks from Controller’s Perspective on State- and Output Feedback Linear Control Systems,” in IEEE Transactions on Industrial Cyber-Physical Systems, doi: 10.1109/TICPS.2025.3615175 This paper demonstrates the fundamental vulnerability of networked linear control systems to perfectly undetectable false data injection attacks (FDIAs)…

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Yingxin’s paper has been published in IEEE T-MRB

Yingxin Qiu, Mengnan Wu, Lena Ting, and Jun Ueda, Two-Stage Optimized Perturbation Design for Efficient Human Arm Impedance Identification with Device Dynamics Compensation, IEEE Transactions on Medical Robotics and Bionics. System identification of human sensorimotor systems requires multiple experimental trials to achieve reliable parameter estimates, yet practical constraints limit the…

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New NSF award for research on cybersecurity in motion control systems

NSF Foundational Research in Robotics (FRR), Geometric Vulnerabilities in Networked Robotic Systems: Analysis of Affine Transformation-Based False Data Injection Attacks and Their Countermeasures (#2516189), PI: Ueda, $691,375, 09/01/2025-08/31/2028 This research develops a comprehensive theoretical framework using Lie group theory and differential geometry to characterize geometric vulnerabilities in networked robotic systems…

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