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Dec. 2022
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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2022> 31(6): 551-558
Xinhao Yan, Siqin Zhuo, Yancheng Wu, Bo Chen. Distributed Privacy-Preserving Fusion Estimation Using Homomorphic Encryption[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2022, 31(6): 551-558. doi: 10.15918/j.jbit1004-0579.2022.072
Citation: Xinhao Yan, Siqin Zhuo, Yancheng Wu, Bo Chen. Distributed Privacy-Preserving Fusion Estimation Using Homomorphic Encryption[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2022, 31(6): 551-558.doi:10.15918/j.jbit1004-0579.2022.072
shu

Distributed Privacy-Preserving Fusion Estimation Using Homomorphic Encryption

doi:10.15918/j.jbit1004-0579.2022.072
  • 1.

    College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China, and also with Zhejiang Provincial United Key Laboratory of Embedded Systems, Hangzhou 310032, China

  • 2.

    College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China

  • 3.

    College of Science, Zhejiang University of Technology, Hangzhou 310023, China

Funds:This work was supported in part by the National Natural Science Foundation of China (No. 61973277), in part by the Zhejiang Provincial Natural Science Foundation of China (No. LR20F030004) and in part by the Major Key Project of PCL (No. PCL2021A09).
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  • Author Bio:

    Xinhao Yanreceived the B.E. degree in communication engineering from Zhejiang University of Technology, Hangzhou, China, in 2020, where he is currently pursuing the M.S. degree in control science and engineering. He was also a visiting scholar with The Hong Kong Polytechnic University, Hong Kong, China, in 2022. His current research interests include distributed estimation, information fusion, networked systems and privacy preservation

    Siqin Zhuois pursuing the B.E. degree in communication engineering at Zhejiang University of Technology, Hangzhou, China. Her current research interests include privacy preservation and Kalman filtering

    Yancheng Wuis pursuing the B.S. degree in information and computing science at Zhejiang University of Technology, Hangzhou, China. Her current research interests include state estimation and privacy preservation

    Bo Chenreceived the B.S. degree in information and computing science from Jiangxi University of Science and Technology, Ganzhou, China, in 2008, and the Ph.D degree in Control Theory and Control Engineering from Zhejiang University of Technology, Hangzhou, China, in 2014. He jointed the Department of Automation, Zhejiang University of Technology in 2018, where he is currently a Professor. He was a Research Fellow with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, from 2014 to 2015 and from 2017 to 2018. He was also a Postdoctoral Research Fellow with the Department of Mathematics, City University of Hong Kong, Hong Kong, from 2015 to 2017. His current research interests include information fusion, distributed estimation and control, networked fusion systems, and secure estimation of cyberphysical systems. Prof. Chen was a recipient of the Outstanding Thesis Award of Chinese Association of Automation in 2015 and also was a recipient of the First Prize of Natural Science of Ministry of Education in 2020. He serves as Associate Editor for IET Control Theory and Applications and Frontiers in Control Engineering

  • Corresponding author:bchen@aliyun.com
  • Received Date:2022-06-30
  • Rev Recd Date:2022-09-08
  • Accepted Date:2022-10-20
  • Publish Date:2022-12-25
    Abstract
  • The privacy-preserving problem for distributed fusion estimation scheme is concerned in this paper. When legitimate user wants to obtain consistent information from multiple sensors, it always employs a fusion center (FC) to gather local data and compute distributed fusion estimates (DFEs). Due to the existence of potential eavesdropper, the data exchanged among sensors, FC and user imperatively require privacy preservation. Hence, we propose a distributed confidentiality fusion structure against eavesdropper by using Paillier homomorphic encryption approach. In this case, FC cannot acquire real values of local state estimates, while it only helps calculate encrypted DFEs. Then, the legitimate user can successfully obtain the true values of DFEs according to the encrypted information and secret keys, which is based on the homomorphism of encryption. Finally, an illustrative example is provided to verify the effectiveness of the proposed methods.
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