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.

翻译：机器人技术、自动化及相关人工智能系统已变得无所不在，引发了对其安全性、可靠性、准确性及可信赖性的担忧。随着与人类密切协作的实体机器人的日益普及，保护这些系统免遭网络攻击（可能导致隐私泄露、关键操作破坏及人身伤害）变得愈发重要。当前能够防御此类系统的专业人才短缺，亟需开发并整合相关课程。本课程描述包含七个自包含自适应模块，主题为"面向泛在机器人系统的AI安全威胁"，具体涵盖：1）引言、攻击案例及动机；2）机器人AI攻击面与渗透测试；3）输入传感器的攻击模式与安全策略；4）训练攻击及相关安全策略；5）推理攻击及相关安全策略；6）执行器攻击及相关安全策略；7）AI、机器人技术与网络安全伦理。