Maxime Cailac

Centre Inria de l'Université de Lorraine

Papers

Total Citations

H-Index

About

Maxime Cailac is a researcher focused on the critical intersection of robotics, cybersecurity, and autonomous systems. His work addresses the often-overlooked vulnerabilities in robotic vision systems, particularly for life-critical applications like self-driving cars. His most cited paper, "Real-Time Attack Detection on Robot Cameras: A Self-Driving Car Application" (2019, 19 citations), provides a structured security analysis of image flows within the Robot Operating System (ROS). This work highlights the persistent neglect of security in robotic camera feeds and proposes methods for real-time attack detection, a foundational contribution to safer autonomous navigation. Cailac’s research is vital for industries deploying ROS in drones and manufacturing, where compromised visual data could lead to catastrophic failures. By exposing these risks and offering detection frameworks, he has helped shape a more security-conscious approach to robotics. His work continues to influence both academic research and practical implementations in autonomous vehicle safety, making him a key voice in the growing field of robotic cybersecurity.