Privacy-Preserving Event-Triggered Quantized Average Consensus

Apostolos I. Rikos, Themistoklis Charalambous, Karl H. Johansson, Christoforos N. Hadjicostis

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

In this paper, we propose a privacy-preserving event-triggered quantized average consensus algorithm that allows agents to calculate the average of their initial values without revealing to other agents their specific value. We assume that agents (nodes) interact with other agents via directed communication links (edges), forming a directed communication topology (digraph). The proposed distributed algorithm can be followed by any agent wishing to maintain its privacy (i.e., not reveal the initial value it contributes to the average) to other, possibly multiple, curious but not malicious agents. Curious agents try to identify the initial values of other agents, but do not interfere in the computation in any other way. We develop a distributed strategy that allows agents while processing and transmitting quantized information, to preserve the privacy of their initial quantized values and at the same time to obtain, after a finite number of steps, the exact average of the initial values of the nodes. Illustrative examples demonstrate the validity and performance of our proposed algorithm.

Original languageEnglish
Title of host publicationProceedings of the 59th IEEE Conference on Decision and Control, CDC 2020
PublisherIEEE
Pages6246-6253
Number of pages8
ISBN (Electronic)9781728174471
DOIs
Publication statusPublished - 14 Dec 2020
MoE publication typeA4 Article in a conference publication
EventIEEE Conference on Decision and Control - Virtual, Online, Jeju Island, Korea, Republic of
Duration: 14 Dec 202018 Dec 2020
Conference number: 59

Publication series

NameProceedings of the IEEE Conference on Decision & Control
PublisherIEEE
ISSN (Print)0743-1546

Conference

ConferenceIEEE Conference on Decision and Control
Abbreviated titleCDC
CountryKorea, Republic of
CityJeju Island
Period14/12/202018/12/2020

Keywords

  • Average consensus
  • Event-triggered
  • Privacy preservation
  • Quantized averaging

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