This article provides a comprehensive and illustrative presentation of the young field of
encrypted control. In particular, we survey the evolution of encrypted controllers from their …

This article begins with an introduction to the modeling of discrete event systems, a class of
dynamical systems with discrete states and event-driven dynamics. It then focuses on logical …

Data-driven systems are gathering increasing amounts of data from users, and sensitive
user data requires privacy protections. In some cases, the data gathered is non-numerical or …

Markov decision processes often seek to maximize a reward function, but onlookers may
infer reward functions by observing agents, which can reveal sensitive information …

A cyber-physical system (CPS) consists of a large number of geographically dispersed
entities and distributed data sharing is necessary to achieve network-wide goals. However …

As members of network systems share more information among agents and with network
providers, sensitive data leakage raises privacy concerns. Motivated by such concerns, we …

Privacy is an important facet of defence against adversaries. In this letter, we introduce the
problem of private flocking. We consider a team of mobile robots flocking in the presence of …

The rapid development of affordable and compact high-fidelity sensors (eg, cameras and
LIDAR) allows robots to construct detailed estimates of their states and environments …

This article introduces and solves a new privacy-related optimization problem for cyber-
physical systems where an adversary tries to learn the system dynamics. In the context of …

In this paper, we study a problem of learning a linear regression model distributively with a
network of N interconnected agents in which each agent can deploy an online learning …