This book addresses privacy in dynamical systems, with applications to smart metering, traffic estimation, and building management.
In the first part, the book explores statistical methods for privacy preservation from the areas of differential privacy and
information-theoretic privacy (e.g., using privacy metrics motivated by mutual information, relative entropy, and Fisher information)
with provable guarantees. In the second part, it investigates the use of homomorphic encryption for the implementation of
control laws over encrypted numbers to support the development of fully secure remote estimation and control. Chiefly intended
for graduate students and researchers, the book provides an essential overview of the latest developments in privacy-aware
design for dynamical systems.