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SDSBT: A Secure Multi-party Data Sharing Platform Based on Blockchain and TEE

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Cyberspace Safety and Security (CSS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12653))

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Abstract

With the rise of big data analytics and artificial intelligence, an increasing number of enterprises and individuals are concerned about the security and privacy of the shared data. However, it is still challenging to achieve a data sharing scheme, which meets the security, privacy, security, and credibility requirements. This paper proposes SDSBT, a multi-party data sharing platform based on blockchain and the trusted execution environment (TEE), which effectively and securely realizes the data sharing among multiple parties. SDSBT achieves the properties including privacy-preserving, identity authentication, application security, and accountability. The security analysis and experimental results show that the scheme is secure and practical.

This study is supported by Oxford-Hainan Blockchain Research Institute, the National Science Foundation of China (No. 61472074, U1708262) and the Fundamental Research Funds for the Central Universities (No. N172304023).

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Authors and Affiliations

  1. Oxford-Hainan Blockchain Research Institute, Chengmai, 571924, China

    Hong Lei, Yun Yan, Zijian Bao, Qinghao Wang & Yongxin Zhang

  2. Department of Computer Science and Engineering, Northeastern University, Shenyang, 110001, China

    Qinghao Wang, Yongxin Zhang & Wenbo Shi

Authors
  1. Hong Lei
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  2. Yun Yan
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  3. Zijian Bao
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  4. Qinghao Wang
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  5. Yongxin Zhang
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  6. Wenbo Shi
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Corresponding author

Correspondence to Qinghao Wang .

Editor information

Editors and Affiliations

  1. Hainan University, Haiukou, China

    Jieren Cheng

  2. Hainan University, Haikou, China

    Xiangyan Tang

  3. Hainan University, Haikou, China

    Xiaozhang Liu

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Lei, H., Yan, Y., Bao, Z., Wang, Q., Zhang, Y., Shi, W. (2021). SDSBT: A Secure Multi-party Data Sharing Platform Based on Blockchain and TEE. In: Cheng, J., Tang, X., Liu, X. (eds) Cyberspace Safety and Security. CSS 2020. Lecture Notes in Computer Science(), vol 12653. Springer, Cham. https://doi.org/10.1007/978-3-030-73671-2_17

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  • DOI: https://doi.org/10.1007/978-3-030-73671-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73670-5

  • Online ISBN: 978-3-030-73671-2

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