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Open Access

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

School of Computer Science, Qufu Normal University, Rizhao 276800, China
Science and Technology Innovation Service Institution of Rizhao, Rizhao 276800, China
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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.

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Tsinghua Science and Technology
Pages 736-752

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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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Received: 19 December 2022
Revised: 12 April 2023
Accepted: 23 May 2023
Published: 04 December 2023
© The Author(s) 2024.

The articles published in this open access journal are distributed under the terms of theCreative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).