Offensive Robot Cybersecurity
V\'ictor Mayoral-Vilches

TL;DR
This paper proposes autonomous offensive cybersecurity strategies for robots using machine learning and game theory, aiming to enhance robotic security through proactive, self-defending mechanisms rooted in system architecture understanding.
Contribution
It introduces a novel architecture for cybersecurity cognitive engines that enable autonomous offensive and defensive strategies in robotic systems.
Findings
Development of security tools for robotic cyber attack simulation
Demonstration of autonomous offensive cybersecurity capabilities
Establishment of a link between robotic architecture and cybersecurity
Abstract
Offensive Robot Cybersecurity introduces a groundbreaking approach by advocating for offensive security methods empowered by means of automation. It emphasizes the necessity of understanding attackers' tactics and identifying vulnerabilities in advance to develop effective defenses, thereby improving robots' security posture. This thesis leverages a decade of robotics experience, employing Machine Learning and Game Theory to streamline the vulnerability identification and exploitation process. Intrinsically, the thesis uncovers a profound connection between robotic architecture and cybersecurity, highlighting that the design and creation aspect of robotics deeply intertwines with its protection against attacks. This duality -- whereby the architecture that shapes robot behavior and capabilities also necessitates a defense mechanism through offensive and defensive cybersecurity…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Malware Detection Techniques
