AI Security Threats against Pervasive Robotic Systems: A Course for Next Generation Cybersecurity Workforce
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Abstract (arXiv)
Robotics, automation, and related Artificial Intelligence (AI) systems have become pervasive bringing in concerns related to security, safety, accuracy, and trust. With growing dependency on physical robots that work in close proximity to humans, the security of these systems is becoming increasingly important to prevent cyber-attacks that could lead to privacy invasion, critical operations sabotage, and bodily harm. The current shortfall of professionals who can defend such systems demands development and integration of such a curriculum. This course description includes details about seven self-contained and adaptive modules on "AI security threats against pervasive robotic systems". Topics include: 1) Introduction, examples of attacks, and motivation; 2) - Robotic AI attack surfaces and penetration testing; 3) - Attack patterns and security strategies for input sensors; 4) - Training attacks and associated security strategies; 5) - Inference attacks and associated security strategies; 6) - Actuator attacks and associated security strategies; and 7) - Ethics of AI, robotics, and cybersecurity.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 12 of its 65 references that are in the map. First posted on arXiv 15 Feb 2023.
Builds on
12 of 65 references.
References · 12
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Citing papers per year: 2023: 1.
1 paper.