Cyber-physical systems, such as those found in autonomous vehicles, drones, medical devices, and power plants, require real-time guarantees to ensure predictable and safe operations. However, this predictability can introduce a hidden security risk: covert timing channels. These are unintended communication channels that allow malicious actors to secretly exchange information between software tasks by manipulating the execution timing. Such vulnerabilities can enable attackers to disrupt normal operations or launch targeted attacks by knowing when critical applications are scheduled to run, posing serious threats to safety and reliability. This CAREER project investigates the existence of covert channels in real-time schedulers and develops strategies to detect, measure, and mitigate them. The success of this project will enhance real-time cyber-physical applications in terms of their security, safety, and resilience. The project's long-term goal is to understand how deterministic behaviors in real-time systems contribute to covert timing vulnerabilities and to develop improved schedulers that can prevent information leaks. By systematically analyzing how timing behaviors in real-time schedulers can be exploited, this study develops new algorithms to detect and mitigate these covert channels. In parallel, the project will devise metrics to quantify information leakage and evaluate the effectiveness of defense strategies. The proposed techniques will be integrated with