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Author:

Lin, Shaofu (Lin, Shaofu.) | Li, Jingwen (Li, Jingwen.) (Scholars:李京文) | Liang, Wei (Liang, Wei.)

Indexed by:

CPCI-S

Abstract:

In recent years, the research and application of blockchain applied in e-government has been increasing. The characteristics of blockchain, such as non-tamper, verifiable and inspirable, have been well applied in confirming the rights, accountability, and assessment of government data resources, and other unresolved problems over the years. Well, the decentralized feature is naturally inconsistent with the strong central feature of the government so that the application of common blockchain technology in e-government cannot support the government regulatory mechanism effectively. To solve this problem, this paper proposes a strong supervision model of blockchain based on the Threshold Ring Signature algorithm (TRS). Further experiments show that the process and results of signature voting by using this model. Compared with the common blockchain, the strong supervision model can control the error rate of the chain information and increase the flexibility of blockchain so as to enhance the integration application of blockchain and e-government.

Keyword:

strong supervision model e-government Blockchain Threshold Ring Signature

Author Community:

  • [ 1 ] [Lin, Shaofu]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 2 ] [Li, Jingwen]Beijing Univ Technol, Fac Informat Technol, Beijing, Peoples R China
  • [ 3 ] [Lin, Shaofu]Beijing Univ Technol, Beijing Inst Smart City, Beijing, Peoples R China
  • [ 4 ] [Liang, Wei]China Telecom Res Inst, Beijing, Peoples R China

Reprint Author's Address:

  • [Liang, Wei]China Telecom Res Inst, Beijing, Peoples R China

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Source :

PROCEEDINGS OF 2020 IEEE 5TH INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC 2020)

Year: 2020

Page: 345-349

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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