An Efficient E-Voting System for Business Intelligence Innovation Based on Blockchain

Haibo Yi ()
Additional contact information
Haibo Yi: Shenzhen Polytechnic

Journal of the Knowledge Economy, 2024, vol. 15, issue 3, No 57, 11533-11547

Abstract: Abstract Business intelligence (BI) is driven by data and provides valuable business insights and decision support through data analysis, mining, and visualization. The application of blockchain technology in electronic voting can make the voting process more fair and transparent. This is because the decentralized nature of blockchain technology ensures that voting data is not lost due to a single central server failure and also mitigates the risk of data tampering. However, electronic voting still faces security issues that are not easily resistant to quantum attacks. To address these challenges, we propose post-quantum cryptography and verifiable random functions for secure and efficient business intelligence electronic voting. Firstly, we propose a post-quantum verifiable random function algorithm that can resist quantum computer attacks. Secondly, we introduce a consensus algorithm based on random functions to achieve fast and efficient consensus. Thirdly, we propose a blockchain architecture based on the consensus algorithm to achieve secure and efficient blockchain applications. By integrating post-quantum verifiable random functions, consensus algorithms, and blockchain technology, we present an efficient business intelligence electronic voting system. Implementation and comparison with relevant designs demonstrate that this system provides efficient and secure electronic voting services for business intelligence users. Furthermore, the efficient consensus algorithm can be utilized to improve other blockchain applications or decentralized applications.

Keywords: Artificial intelligence (AI); Business intelligence (BI); Inovation management; E-voting; Blockchain (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s13132-023-01560-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jknowl:v:15:y:2024:i:3:d:10.1007_s13132-023-01560-x

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/13132

DOI: 10.1007/s13132-023-01560-x

Access Statistics for this article

Journal of the Knowledge Economy is currently edited by Elias G. Carayannis

More articles in Journal of the Knowledge Economy from Springer, Portland International Center for Management of Engineering and Technology (PICMET)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().