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Blockchain Data Privacy Access Control Based on Searchable Attribute Encryption

Tao Feng1,*, Hongmei Pei1, Rong Ma1, Youliang Tian2, Xiaoqin Feng3

1 Lanzhou University of Technology, Lanzhou, 730050, China
2 College of Computer Science and Technology, Guizhou University, Guizhou, China
3 School of Computer, Xiandian University, Xi’an, China

* Corresponding Author: Tao Feng. Email:

Computers, Materials & Continua 2021, 66(1), 871-890.


Data privacy is important to the security of our society, and enabling authorized users to query this data efficiently is facing more challenge. Recently, blockchain has gained extensive attention with its prominent characteristics as public, distributed, decentration and chronological characteristics. However, the transaction information on the blockchain is open to all nodes, the transaction information update operation is even more transparent. And the leakage of transaction information will cause huge losses to the transaction party. In response to these problems, this paper combines hierarchical attribute encryption with linear secret sharing, and proposes a blockchain data privacy protection control scheme based on searchable attribute encryption, which solves the privacy exposure problem in traditional blockchain transactions. The user’s access control is implemented by the verification nodes, which avoids the security risks of submitting private keys and access structures to the blockchain network. Associating the private key component with the random identity of the user node in the blockchain can solve the collusion problem. In addition, authorized users can quickly search and supervise transaction information through searchable encryption. The improved algorithm ensures the security of keywords. Finally, based on the DBDH hypothesis, the security of the scheme is proved in the random prediction model.


Cite This Article

T. Feng, H. Pei, R. Ma, Y. Tian and X. Feng, "Blockchain data privacy access control based on searchable attribute encryption," Computers, Materials & Continua, vol. 66, no.1, pp. 871–890, 2021.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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