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A Trustworthy Decentralized System for Health Data Integration and Sharing: Design and Experimental Validation

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HCI for Cybersecurity, Privacy and Trust (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14045))

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Abstract

Personal health data collected via wearable devices can be used for sharing and utilization to provide smart healthcare services. Since personal health data involves sensitive information, it is necessary to require a secure way to manage and use data with the consent of each individual. To integrate and share health data securely, many frameworks using federated learning and blockchain-based system have been proposed. However, the issues of ensuring data ownership and enhancing privacy protection remain to be solved. In this paper, we propose a trustworthy system for health data integration and sharing enabled by decentralized federated learning. We describe the major functions and features, including health data integration, doubling data ownership, data analysis via decentralized federated learning, and incentive mechanisms. We further introduce the experiment and assume two application scenarios for sharing and utilization of personal health data and visualization feedback to users. Various types of health data are collected and integrated into the system with decentralized data analysis while sharing results and models and reducing data transmission for privacy-preserving. The proposed system can be expected to provide an effective way to integrate and analyze personal health data for personalized smart healthcare.

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Acknowledgement

The work was supported in part by 2022–2024 Masaru Ibuka Foundation Research Project on Oriental Medicine, 2020–2025 JSPS A3 Foresight Program (Grant No. JPJSA3F20200001), 2022 Waseda University Grants for Special Research Projects (Nos. 2022C-225 and 2022R-036), 2020–2021 Waseda University-NICT Matching Funds Program, 2022 JST SPRING (Grant No. JPMJSP2128), and 2022 Waseda University Advanced Research Center for Human Sciences Project (Grant No. BA080Z000300).

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Authors and Affiliations

  1. Graduate School of Human Sciences, Waseda University, Tokorozawa, Japan

    Ruichen Cong & Yuxi Li

  2. Zhejiang Chinese Medical University, Hangzhou, China

    Yaping Ye, Jianlun Wu, Yuerong Chen & Yishan Bian

  3. Department of Information and Network Science, Chiba Institute of Technology, Narashino, Japan

    Kiichi Tago

  4. Faculty of Human Sciences, Waseda University, Tokorozawa, Japan

    Shoji Nishimura, Atsushi Ogihara & Qun Jin

Authors
  1. Ruichen Cong
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  2. Yaping Ye
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  3. Jianlun Wu
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  4. Yuxi Li
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  5. Yuerong Chen
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  6. Yishan Bian
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  7. Kiichi Tago
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  8. Shoji Nishimura
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  9. Atsushi Ogihara
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  10. Qun Jin
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Corresponding author

Correspondence to Qun Jin .

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Editors and Affiliations

  1. San Jose State University, San Jose, CA, USA

    Abbas Moallem

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Cong, R. et al. (2023). A Trustworthy Decentralized System for Health Data Integration and Sharing: Design and Experimental Validation. In: Moallem, A. (eds) HCI for Cybersecurity, Privacy and Trust. HCII 2023. Lecture Notes in Computer Science, vol 14045. Springer, Cham. https://doi.org/10.1007/978-3-031-35822-7_9

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  • DOI: https://doi.org/10.1007/978-3-031-35822-7_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35821-0

  • Online ISBN: 978-3-031-35822-7

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