Security and Privacy in Control

Mobile robots, such as autonomous cars, vessels, and drones, can significantly improve our quality of life. These robots are equipped with communication units that allow information sharing and coordination near humans, abilities that are fundamental to improve, for example, traffic efficiency and even save human lives. However, the occurrence of attacks can severely disrupt the coordination with negative consequences on humans and their security. Furthermore, to coordinate, the robots share private information, such as habits, routes, and destinations, which may be inadvertently exposed to prying eyes. Hence, there is an urgent need to address these security and privacy concerns for our society to fully benefit from multi-robot systems.

The goal of this course is to provide the students with (i) an overview of the state of the art in security and privacy from the perspective of control and robotics applications, and (ii) the basics to use state-of-the-art tools to design secure and privacy-preserving control algorithms.

The course spans over the following main topics:

1) differential privacy and its applications to control.

2) applied cryptography (basics and more advanced concepts, such as secret sharing, garbled circuits, and secure multiparty computation) with some examples of applications to control systems.

3) an overview on the more general security aspects for control systems (discussion on the challenges and some applications based on recent research in the CS and control communities).