The field of cyber-physical systems security and control is rapidly evolving, with a focus on developing innovative solutions to protect against increasingly sophisticated threats. Recent research has emphasized the importance of game-theoretic approaches, stochastic control, and reinforcement learning to enhance the resilience and security of these systems. Notable advances include the development of hierarchical and decentralized control architectures, as well as the integration of physical constraints and uncertainty modeling into control algorithms. These advancements have significant implications for the security and reliability of critical infrastructure, such as industrial control systems and autonomous vehicles. Noteworthy papers include: CyGym, which introduces a simulation-based game-theoretic analysis framework for cybersecurity. ARMOR, which presents a robust reinforcement learning-based control framework for UAVs under physical attacks. Beyond Interval MDPs, which proposes a unified abstraction framework for control synthesis in stochastic systems with probabilistic guarantees.