Guaranteed Privacy-Preserving Hinfty-Optimal Interval Observer Synthesis for Bounded-Error LTI SystemsOptimal control for nonholonomic systems with symmetry

Mohammad Khajenejad and Sonia Martínez
Proceedings of the 2024 American Control Conference, submitted

Abstract:

This paper furthers current research into the notion of guaranteed privacy, which provides a deterministic characterization of the privacy of ouput signals of a dynamical system or mechanism. Unlike stochastic differential privacy, guaranteed privacy offers strict bounds on the proximity between the ranges of two sets of estimated data. Our approach relies on synthesizing an interval observer that incorporates bounded noise perturbation factors and an observer gain. This observer simultaneously provides guaranteed private and stable interval-valued estimates for the desired variable. We demonstrate the optimality of our design by minimizing the Hinfty norm of the observer error system. Lastly, we assess the accuracy of our proposed mechanism by quantifying the loss incurred when considering guaranteed privacy specifications, and illustrate our approach outperformance to differential privacy through simulations.

File: main.pdf

Bib-tex entry:

@InProceedings{MK-SM:24-acc,
author = {M. Khajenejad and S. Mart{\'\i}nez},
title = {},
booktitle = {2024 American Control Conference},
pages = {},
year = {2024},
address = {},
month = {}
}