In telerobotic applications, human operators interact with robots through a computer network. This project is developing tools to prevent security threats in telerobotics, by monitoring and detecting malicious activities and correcting for them. To develop tools to prevent and mitigate security threats against telerobotic systems, this project adapts cybersecurity methods and extends them to cyber-physical systems. Knowledge about physical constraints and interactions between the cyber and physical components of the system are leveraged for security. A monitoring system is developed which collects operator commands and robot feedback information to perform real-time verification of the operator. Timely and reliable detection of any discrepancy between real and spoofed operator movements enables quick detection of adversarial activities. The results are evaluated on the UW-developed RAVEN surgical robot. This project brings together research in robotics, computer and network security, control theory and machine learning, in order to gain better understanding of complex teleoperated robotic systems and to engineer telerobotic systems that provide strict safety, security and privacy guarantees. The results are relevant and applicable to a wide range of applications, including telerobotic surgery, search and rescue missions, military operations, underwater infrastructure and repair, cleanup and repair in hazardous environments, mining, as well as manipulation/inspections of objects in low earth orbit. The project algorithms, software and hardware are being made available to the non-profit cyber-physical research community. Graduate and undergraduate students are being trained in cyber-physical systems security topics, and K-12, community college students and under-represented minority students are being engaged.