Convex Optimisation-Based Privacy-Preserving Distributed Average Consensus in Wireless Sensor Networks

Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

In many applications of wireless sensor networks, it is important that the privacy of the nodes of the network be protected. Therefore, privacy-preserving algorithms have received quite some attention recently. In this paper, we propose a novel convex optimization-based solution to the problem of privacy-preserving distributed average consensus. The proposed method is based on the primal-dual method of multipliers (PDMM), and we show that the introduced dual variables of the PDMM will only converge in a certain subspace determined by the graph topology and will not converge in the orthogonal complement. These properties are exploited to protect the private data from being revealed to others. More specifically, the proposed algorithm is proven to be secure for both passive and eavesdropping adversary models. Finally, the convergence properties and accuracy of the proposed approach are demonstrated by simulations which show that the method is superior to the state-of-the-art.
Original languageEnglish
Title of host publicationICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Subtitle of host publicationProceedings
PublisherIEEE
Pages5895-5899
Number of pages5
ISBN (Electronic)978-1-5090-6631-5
ISBN (Print)978-1-5090-6632-2
DOIs
Publication statusPublished - 2020
EventICASSP 2020: IEEE International Conference on Acoustics, Speech and Signal Processing - Barcelona, Spain
Duration: 4 May 20208 May 2020

Conference

ConferenceICASSP 2020
CountrySpain
CityBarcelona
Period4/05/208/05/20

Keywords

  • Distributed average consensus
  • convex optimisation
  • primal-dual method of multipliers
  • privacy
  • wireless sensor networks

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    Li, Q., Heusdens, R., & Christensen, M. G. (2020). Convex Optimisation-Based Privacy-Preserving Distributed Average Consensus in Wireless Sensor Networks. In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): Proceedings (pp. 5895-5899). IEEE. https://doi.org/10.1109/ICASSP40776.2020.9053348