Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …

Control as a Service (CaaS) is becoming a reality-particularly in the case of building
automation and smart grid management. Often, the control algorithms in CaaS focus on …

As large amounts of data are circulated both from users to a cloud server and between
users, privately aggregating the shared data is critical. This article considers the problem of …

Encrypted control is a promising method for the secure outsourcing of controller computation
to a public cloud. However, a feasible method for security proofs of control has not yet been …

We provide an efficient and private solution to the problem of encryption-aware data-driven
control. We investigate a Control as a Service scenario, where a client employs a …

This study considers encrypting a gain-scheduled controller for polytopic linear parameter
varying systems by reconstructing the controller with the linear controller configuration. An …

With the fast growth of quantum computers in recent years, the use of post-quantum
cryptography has steadily become vital. In the privacy-preserving aggregation of federated …

Security and privacy are significant concerns in realizing dependable cyberphysical
systems. To ensure the security and privacy of these systems, systems and control …

Privacy-Preserving Machine Learning (PPML) has received much attention from the
machine learning community, from academic researchers to industry practitioners to …