Rodrigo Antunes

Papers

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About

Rodrigo Antunes is a researcher specializing in cybersecurity for robotic systems, with a particular focus on the intersection of machine learning and autonomous robot security. His work addresses the growing vulnerability of modern robotic platforms to cyber threats, recognizing that as robots increasingly share physical spaces with humans, the security risks associated with their underlying computing infrastructure become critically important. Antunes' most notable contribution, "Detecting Data Injection Attacks in ROS Systems using Machine Learning" (2022), tackles the specific challenge of identifying malicious data injection attacks within the Robot Operating System (ROS), one of the most widely adopted frameworks in robotics development. By applying machine learning techniques to detect these intrusions, his research bridges two rapidly evolving fields — robotics and cybersecurity — offering practical defensive mechanisms for real-world robotic deployments. This work has garnered 7 citations since its publication, reflecting growing scholarly interest in securing autonomous systems against novel attack vectors. His research is particularly timely given the accelerating deployment of robots in industrial, healthcare, and domestic environments, where security breaches could carry serious physical consequences. Antunes' contributions provide a foundational framework for researchers and engineers working to make robotic systems more resilient against emerging cyber threats.