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

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Author(s)
Fiore, Davide 
Russo, Giovanni 
Uri
http://hdl.handle.net/10197/12285
Date Issued
August 2019
Date Available
22T15:33:55Z June 2021
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.
Sponsorship
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 systems

  • Resilient consensus

  • Differential privacy

  • Networked control sys...

DOI
10.1016/j.automatica.2019.04.029
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
I-Form Research Collection
Scopus© citations
39
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Feb 1, 2023
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