A Privacy-Preserving Asynchronous Averaging Algorithm based on Shamir’s Secret Sharing

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Average consensus is widely used in information fusion, and it requires information exchange between a set of nodes to achieve an agreement. Unfortunately, the information exchange may disclose the individual's private information, and this raises serious concerns for individual privacy in some applications. Hence, a privacy-preserving asynchronous averaging algorithm is proposed in this paper to maintain the privacy of each individual using Shamir's secret sharing scheme, as known from secure multiparty computation. The proposed algorithm is based on a lightweight cryptographic technique. It gives identical accuracy solution as the non-privacy concerned algorithm and achieves perfect security in clique-based networks without the use of a trusted third party. In each iteration of the algorithm, each individual's privacy in the selected clique is protected under a passive attack where the adversary controls some of the nodes. Finally, it also achieves robustness of up to one third transmission error.

Original languageEnglish
Title of host publication27th European Signal Processing Conference
Number of pages5
PublisherIEEE Signal Processing Society
Publication dateSep 2019
Article number8903166
ISBN (Electronic)9789082797039
Publication statusPublished - Sep 2019
Event27th European Signal Processing Conference, EUSIPCO 2019 - Coruña, Spain
Duration: 2 Sep 20196 Sep 2019


Conference27th European Signal Processing Conference, EUSIPCO 2019
SeriesProceedings of the European Signal Processing Conference


  • Active attack
  • Distributed average consensus
  • Privacy-preserving
  • Secure multiparty computation
  • Shamir's secret sharing

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