Cyber-physical systems (CPS), powered by emerging artificial intelligence (AI) technologies, have become integral to various critical domains such as the Internet of Things (IoTs), medical devices, and autonomous vehicles. A unique aspect of these systems lies in their interactions with the physical world, by perceiving environments through heterogeneous modalities (perception), processing digital data with intelligence algorithms (computing), and autonomously actuating controls that affect physical processes (actuation). While this intricate fusion of cyber and physical components has unlocked unprecedented capabilities, it has also introduced new security challenges. However, traditional security measures often fall short in addressing these multifaceted threats. Under this paradigm shift, I systematically explore and mitigate the threats inherent in AI-enabled cyber-physical systems. The research objectives are threefold: (1) investigating how the interplay of cyber and physical components opens up novel attack and defense vectors, (2) developing robust defense strategies grounded by physical laws and reasoning, and (3) benchmarking and theoretically analyzing security trade-offs from algorithmic, system-level, and human-centric perspectives. By bridging the gap between cyber and physical domains, my research enhances the resilience and trustworthiness of modern CPS while retaining system efficiency and usability.