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).

· Written review of 3 papers of choice (1 paper from differential privacy, 1 paper from cryptography, and 1 paper from security) using the provided form and discussion of the paper with their peers during a debate lecture. The preparation of the debate lecture consists of a short presentation in pairs with a colleague on the same selected paper, in which one student discusses the pros of the approach and the other student discusses the cons of the approach. The attendance at the debate lecture is mandatory. [1 EC, 40% of the final grade, mandatory to complete the course];

· Practical assignments in the form of short written reports in PDF format that contain a reflection on the results with plots supporting the statements and accompanied by the code used to solve the assignments (e.g., using Python, SPDZ, and MATLAB). The assignments should be submitted within the indicated deadlines by the lecturer. [1 EC, 40% of the final grade, mandatory to complete the course];

· Final oral exam (a written exam will be considered only if the number of students is too large); to access the final exam, each student should have completed and submitted within the deadlines indicated by the lecturer the reviews, the programming assignments, and the debate. [1 EC, 20% of the final grade, mandatory to complete the course].