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Tsinghua Science and Technology 2024, 29(3): 736-752 https://doi.org/10.26599/TST.2023.9010049
Open Access | Issue | Published: 04 December 2023

Effective Identity Authentication Based on Multiattribute Centers for Secure Government Data Sharing

Show Author's Information Meiquan Wang1,  Junhua Wu1( ),  Tongdui Zhang2,  Junhao Wu1,  Guangshun Li1
School of Computer Science, Qufu Normal University, Rizhao 276800, China
Science and Technology Innovation Service Institution of Rizhao, Rizhao 276800, China
Keywords:
distribution, identity authentication, blockchain, dynamic key generation
Cite this article:
Wang M, Wu J, Zhang T, et al. Effective Identity Authentication Based on Multiattribute Centers for Secure Government Data Sharing. Tsinghua Science and Technology, 2024, 29(3): 736-752. https://doi.org/10.26599/TST.2023.9010049
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Abstract Full text About this article

As one of the essential steps to secure government data sharing, Identity Authentication (IA) plays a vital role in the processing of large data. However, the centralized IA scheme based on a trusted third party presents problems of information leakage and single point of failure, and those related to key escrow. Therefore, herein, an effective IA model based on multiattribute centers is designed. First, a private key of each attribute of a data requester is generated by the attribute authorization center. After obtaining the private key of attribute, the data requester generates a personal private key. Second, a dynamic key generation algorithm is proposed, which combines blockchain and smart contracts to periodically update the key of a data requester to prevent theft by external attackers, ensure the traceability of IA, and reduce the risk of privacy leakage. Third, the combination of blockchain and interplanetary file systems is used to store attribute field information of the data requester to further reduce the cost of blockchain information storage and improve the effectiveness of information storage. Experimental results show that the proposed model ensures the privacy and security of identity information and outperforms similar authentication models in terms of computational and communication costs.


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About this article

Effective Identity Authentication Based on Multiattribute Centers for Secure Government Data Sharing

Show Author's information Meiquan Wang1, Junhua Wu1( ), Tongdui Zhang2, Junhao Wu1, Guangshun Li1
School of Computer Science, Qufu Normal University, Rizhao 276800, China
Science and Technology Innovation Service Institution of Rizhao, Rizhao 276800, China

Abstract

As one of the essential steps to secure government data sharing, Identity Authentication (IA) plays a vital role in the processing of large data. However, the centralized IA scheme based on a trusted third party presents problems of information leakage and single point of failure, and those related to key escrow. Therefore, herein, an effective IA model based on multiattribute centers is designed. First, a private key of each attribute of a data requester is generated by the attribute authorization center. After obtaining the private key of attribute, the data requester generates a personal private key. Second, a dynamic key generation algorithm is proposed, which combines blockchain and smart contracts to periodically update the key of a data requester to prevent theft by external attackers, ensure the traceability of IA, and reduce the risk of privacy leakage. Third, the combination of blockchain and interplanetary file systems is used to store attribute field information of the data requester to further reduce the cost of blockchain information storage and improve the effectiveness of information storage. Experimental results show that the proposed model ensures the privacy and security of identity information and outperforms similar authentication models in terms of computational and communication costs.

Keywords: distribution, identity authentication, blockchain, dynamic key generation

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Publication history
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Publication history

Received: 19 December 2022
Revised: 12 April 2023
Accepted: 23 May 2023
Published: 04 December 2023
Issue date: June 2024

Copyright

© The Author(s) 2024.

Acknowledgements

Acknowledgment

This work was supported by the National Natural Science Foundation of China (Nos. 61771289 and 61832012), the Natural Science Foundation of Shandong Province (Nos. ZR2021QF050 and ZR2021MF075), the Shandong Natural Science Foundation Major Basic Research (No. ZR2019ZD10), the Shandong Key Research and Development Program (No. 2019GGX1050), and the Shandong Major Agricultural Application Technology Innovation Project (No. SD2019NJ007).

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