# Geometric Vulnerabilities in Networked Robotic Systems: Analysis of Affine Transformation-Based False Data Injection Attacks and Their Countermeasures

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · Georgia Tech Research Corporation (GA) · $691,375

## Abstract

This award supports research that addresses critical vulnerabilities in remotely controlled robotic systems through a comprehensive study of a particularly sophisticated class of cyber attacks, thereby advancing the national health, promoting the progress of science, advancing prosperity and welfare, and securing the national defense. Modern robotic systems rely heavily on networked communication for coordination and control, creating opportunities for malicious actors to inject false data that can cause robots to perform unintended and potentially dangerous actions. Traditional cybersecurity approaches designed for computer networks are insufficient for robotic systems because robots operate in physical environments where security breaches can result in property damage, personal injury, or disruption of essential services. This project looks to address this critical gap by studying affine transformation-based perfectly undetectable attacks that exploit the geometric properties inherent in robotic systems to remain completely undetectable by conventional security measures. Understanding and defending against these attacks is crucial for maintaining public trust in robotic technologies and ensuring their safe deployment in critical applications. The project seeks to advance fundamental knowledge in robotic cybersecurity while training graduate students in interdisciplinary research combining robotics, cybersecurity, and mathematical theory, thereby strengthening the national w

## Key facts

- **NSF award ID:** 2516189
- **Awardee organization:** Georgia Tech Research Corporation (GA)
- **SAM.gov UEI:** EMW9FC8J3HN4
- **PI:** Jun Ueda
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CONTROL SYSTEMS, Cyber-Physical Systems, ROBOTICS
- **Estimated total:** $691,375
- **Funds obligated:** $691,375
- **Transaction type:** Standard Grant
- **Period:** 09/01/2025 → 08/31/2028

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2516189

## Citation

> US National Science Foundation, Award 2516189, Geometric Vulnerabilities in Networked Robotic Systems: Analysis of Affine Transformation-Based False Data Injection Attacks and Their Countermeasures. Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2516189. Licensed CC0.

---

*[NSF Awards dataset](/datasets/nsf-awards) · CC0 1.0*