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Autori principali: Liu, Le, Kawano, Yu, Xie, Antai, Cao, Ming
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2503.24089
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author Liu, Le
Kawano, Yu
Xie, Antai
Cao, Ming
author_facet Liu, Le
Kawano, Yu
Xie, Antai
Cao, Ming
contents In this paper, we investigate initial state privacy protection for discrete-time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances. A new differential privacy condition is formulated using incremental output boundedness, enabling the design of time-varying Laplacian noise to achieve specified privacy guarantees. The proposed framework extends beyond initial state protection to also cover system parameter privacy, which is demonstrated as a special application.
format Preprint
id arxiv_https___arxiv_org_abs_2503_24089
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
Liu, Le
Kawano, Yu
Xie, Antai
Cao, Ming
Systems and Control
In this paper, we investigate initial state privacy protection for discrete-time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances. A new differential privacy condition is formulated using incremental output boundedness, enabling the design of time-varying Laplacian noise to achieve specified privacy guarantees. The proposed framework extends beyond initial state protection to also cover system parameter privacy, which is demonstrated as a special application.
title Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
topic Systems and Control
url https://arxiv.org/abs/2503.24089