Minimum-norm Sparse Perturbations for Opacity in Linear Systems
Abstract
Opacity is a notion that describes an eavesdropper's inability to estimate a system's 'secret' states by observing the system's outputs. In this paper, we propose algorithms to compute the minimum sparse perturbation to be added to a system to make its initial states opaque. For these perturbations, we consider two sparsity constraints - structured and affine. We develop an algorithm to compute the global minimum-norm perturbation for the structured case. For the affine case, we use the global minimum solution of the structured case as initial point to compute a local minimum. Empirically, this local minimum is very close to the global minimum. We demonstrate our results via a running example.
Cite
@article{arxiv.2306.17606,
title = {Minimum-norm Sparse Perturbations for Opacity in Linear Systems},
author = {Varkey M John and Vaibhav Katewa},
journal= {arXiv preprint arXiv:2306.17606},
year = {2023}
}
Comments
Submitted to Indian Control Conference, 2023 (6 pages)