2 citations · 3 across the 7 of their papers we have counts for
8 papers
Immersion and Invariance-based Coding for Privacy-Preserving Federated Learning
Haleh Hayati, Carlos Murguia, Nathan van de Wouw
Federated learning (FL) has emerged as a method to preserve privacy in collaborative distributed learning. In FL, clients train AI models directly on their devices rather than shar…
Privacy in Cloud Computing through Immersion-based Coding
Haleh Hayati, Nathan van de Wouw, Carlos Murguia
Cloud computing enables users to process and store data remotely on high-performance computers and servers by sharing data over the Internet. However, transferring data to clouds c…
Infinite Horizon Privacy in Networked Control Systems: Utility/Privacy Tradeoffs and Design Tools
Haleh Hayati, Nathan van de Wouw, Carlos Murguia
We address the problem of synthesizing distorting mechanisms that maximize infinite horizon privacy for Networked Control Systems (NCSs). We consider stochastic LTI systems where i…
Immersion and Invariance-based Coding for Privacy in Remote Anomaly Detection
Haleh Hayati, Nathan van de Wouw, Carlos Murguia
We present a framework for the design of coding mechanisms that allow remotely operating anomaly detectors in a privacy-preserving manner. We consider the following problem setup.…
Privacy-Preserving Anomaly Detection in Stochastic Dynamical Systems: Synthesis of Optimal Gaussian Mechanisms
Haleh Hayati, Carlos Murguia, Nathan van de Wouw
We present a framework for designing distorting mechanisms that allow remotely operating anomaly detectors while preserving privacy. We consider the problem setting in which a remo…
Privacy-Preserving Federated Learning via System Immersion and Random Matrix Encryption
Haleh Hayati, Carlos Murguia, Nathan van de Wouw
Federated learning (FL) has emerged as a privacy solution for collaborative distributed learning where clients train AI models directly on their devices instead of sharing their da…
Gaussian Mechanisms Against Statistical Inference: Synthesis Tools
Haleh Hayati, Carlos Murguia, Nathan van de Wouw
In this manuscript, we provide a set of tools (in terms of semidefinite programs) to synthesize Gaussian mechanisms to maximize privacy of databases. Information about the database…
Finite Horizon Privacy of Stochastic Dynamical Systems: A Synthesis Framework for Dependent Gaussian Mechanisms
Haleh Hayati, Carlos Murguia, Nathan van de Wouw
We address the problem of synthesizing distorting mechanisms that maximize privacy of stochastic dynamical systems. Information about the system state is obtained through sensor me…