Resilient consensus for multi-agent systems subject to differential privacy requirements

Files in This Item:
 File SizeFormat
DownloadResilient consensus for multi-agent ssytems subject to.....pdf545.69 kBAdobe PDF
Title: Resilient consensus for multi-agent systems subject to differential privacy requirements
Authors: Fiore, DavideRusso, Giovanni
Permanent link:
Date: Aug-2019
Online since: 2021-06-22T15:33:55Z
Abstract: We consider multi-agent systems interacting over directed network topologies where a subset of agents is adversary/faulty and where the non-faulty agents have the goal of reaching consensus, while fulfilling a differential privacy requirement on their initial conditions. To address this problem, we develop an update law for the non-faulty agents. Specifically, we propose a modification of the so-called Mean-Subsequence-Reduced (MSR) algorithm, the Differentially Private MSR (DP-MSR) algorithm, and characterize three important properties of the algorithm: correctness, accuracy and differential privacy. We show that if the network topology is -robust, then the algorithm allows the non-faulty agents to reach consensus despite the presence of up to faulty agents and we characterize the accuracy of the algorithm. Furthermore, we also show in two important cases that our distributed algorithm can be tuned to guarantee differential privacy of the initial conditions and the differential privacy requirement is related to the maximum network degree. The results are illustrated via simulations.
Funding Details: Science Foundation Ireland
Type of material: Journal Article
Publisher: Elsevier
Journal: Automatica
Volume: 106
Start page: 18
End page: 26
Copyright (published version): 2019 Elsevier
Keywords: Multi-agent systemsResilient consensusDifferential privacyNetworked control systems
DOI: 10.1016/j.automatica.2019.04.029
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License:
Appears in Collections:Electrical and Electronic Engineering Research Collection
I-Form Research Collection

Show full item record

Page view(s)

Last Week
Last month
checked on Jul 31, 2021


checked on Jul 31, 2021

Google ScholarTM



If you are a publisher or author and have copyright concerns for any item, please email and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.