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Resilient consensus for multi-agent systems subject to differential privacy requirements
Author(s)
Date Issued
2019-06-28
Date Available
2021-08-20T15:48:54Z
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 (2f +1)-robust, then the algorithm allows the non-faulty agents to reach consensus despite the presence of up to f 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 guarantees 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
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2019 EUCA
Web versions
Language
English
Status of Item
Peer reviewed
Conference Details
The 2019 18th European Control Conference (ECC), Naples, Italy, 25-28 June 2021
This item is made available under a Creative Commons License
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