Automation is being increasingly introduced into every man-made system. The thrust to achieve trustworthy autonomous systems, which can attain goals independently in the presence of significant uncertainties and for long periods of time without any human intervention, has always been enticing. Significant progress has been made in the avenues of both software and hardware for meeting these objectives. However, technological challenges still exist and particularly in terms of decision making under uncertainty. In an autonomous system, uncertainties can arise from the operating environment, adversarial attacks, and from within the system. While a lot of work has been done on ensuring safety of systems under standard sensing errors, much less attention has been given on securing it and its sensors from attacks. As such, autonomous cyber-physical systems (CPS), which rely heavily on sensing units for decision making, remain vulnerable to such attacks. Given the fact that the age of autonomous CPS is upon us and their influence is gradually increasing, it becomes an urgent task to develop effective solutions to ensure the security and trustworthiness of autonomous CPS under adversarial attacks. The researchers of this project provide a comprehensive real-time, resource-aware solution for detection and recovery of autonomous CPS from physical and cyber-attacks. This project also includes effort to educate and prepare the community for the potential cyber and physical threats on autonomous CPS. With the observation that a thorough security certification of autonomous CPS will provide formal evaluation of autonomous CPS, the researchers in this project intend to develop methods to facilitate manufacturers for certifying security solutions. Toward this goal, the researchers will first develop new theories to understand the impact of physical and cyber-attack on system level properties such as controllability, stability, and safety. They will then develop algorithms for detection and recovery of CPS from physical attacks on active sensors. The proposed recovery method will ensure the integrity of sensor measurements when the system is under attack. Furthermore, a new analysis framework will be constructed that uses platform-based design methodology to represent the CPS and verifies it against design metric constraints such as security, timing, resource, and performance. The key contributions of this project towards autonomous CPS security certification include 1) a comprehensive study of relationship between attacks and system-level properties; 2) algorithms and their optimization for detection and automatic recovery of autonomous CPS from attacks; and 3) systematically quantifying impact of security on design metrics.