Modern-day control applications increasingly rely on cyber-physical systems (CPS) to implement advanced functionalities. Notable examples within automotive domains include adaptive cruise control, intelligent navigation, and autonomous driving. Leveraging the cloud's virtually infinite storage and computational power proves to be an efficient strategy for executing these sophisticated control algorithms. However, migrating control computations to the cloud introduces new challenges, notably on security and real-time constraints. We will present an integrated design and optimization methodology tailored for cloud-based control systems. This approach addresses security concerns and other crucial CPS design prerequisites, particularly focusing on ensuring the security and stability mandates of control loops closed over the cloud.