Blockchain-Based Electoral Systems as a Remedy for Electoral Fraud: Evidence from Nigeria's Democratic Experience

Electoral integrity remains one of the most critical challenges confronting emerging democracies, particularly in sub-Saharan Africa. This article examines the viability of Hyperledger Fabric blockchain technology as a systemic solution to the pervasive electoral fraud, institutional distrust, and process opacity that have undermined democratic governance in Nigeria. Drawing on primary survey data collected from 800 Nigerian voters across all 36 states and the Federal Capital Territory, this study analyses public perceptions of the Independent National Electoral Commission (INEC), identifies the structural weaknesses in Nigeria's electoral framework, and evaluates the technical architecture of a proposed blockchain-based voting system. Survey results reveal that approximately 65% of respondents attribute electoral failures primarily to INEC, while over 85% expressed no confidence in the commission's ability to conduct transparent elections. Respondents overwhelmingly called for tamper-proof, technology-driven electoral systems. The proposed Hyperledger Fabric-based system, incorporating biometric authentication, decentralised ledger technology, and real-time result transmission, is posited as a cost-effective and structurally sound alternative to existing electoral infrastructure. At an estimated implementation cost of approximately 100 billion Naira a fraction of the 400+ billion Naira spent in the 2023 general elections the system offers significant fiscal and democratic value. The article concludes with policy recommendations for institutional reform, regulatory alignment, and phased technological adoption.

Blockchain technology, electoral integrity, Hyperledger Fabric, Nigeria, INEC, democratic governance, biometric authentication

1. Adejumobi, S. (2007). Elections in Africa: A fading shadow of democracy? International Political Science Review, 21(1), 59–73. https://doi.org/10.1177/0192512100021001004 [Google Scholar] [Crossref]

2. Agbu, O. (2016). Electoral management bodies and democratization in Africa. In O. Agbu (Ed.), Elections and democratization in West Africa: 1990-2009 (pp. 45–78). CODESRIA. [Google Scholar] [Crossref]

3. Bratton, M. (2008). Vote buying and violence in Nigerian election campaigns. Electoral Studies, 27(4), 621–632. https://doi.org/10.1016/j.electstud.2008.04.013 [Google Scholar] [Crossref]

4. Castillo, M. (2020, November 3). How to track official election results on Ethereum and EOS. Forbes. https://www.forbes.com/sites/michaeldelcastillo/2020/11/03/how-to-track-official-election-results-on-ethereum-and-eos/ [Google Scholar] [Crossref]

5. Cheeseman, N., & Klaas, B. (2018). How to rig an election. Yale University Press. [Google Scholar] [Crossref]

6. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008 [Google Scholar] [Crossref]

7. Desouza, K. C., & Somvanshi, K. K. (2018, May 30). How blockchain could help improve election transparency. Brookings Institution. https://www.brookings.edu/articles/how-blockchain-could-improve-election-transparency/ [Google Scholar] [Crossref]

8. Easton, D. (1975). A re-assessment of the concept of political support. British Journal of Political Science, 5(4), 435–457. https://doi.org/10.1017/S0007123400008309 [Google Scholar] [Crossref]

9. European Union Election Observation Mission. (2023). European Union Election Observation Mission Nigeria 2023 final report. European External Action Service. https://www.eeas.europa.eu/sites/default/files/documents/2023/EU%20EOM%20Nigeria%202023%20Final%20Report%20EN.pdf [Google Scholar] [Crossref]

10. Igwebuike, A. C. N. (2023). Proposal for the adoption and implementation of blockchain technology in regional and national elections in Nigeria [Capstone project report, Guglielmo Marconi University / Athena Global Education]. [Google Scholar] [Crossref]

11. Jefferson, D., & Verified Voting. (2023). The myth of "secure" blockchain voting. U.S. Vote Foundation. https://www.usvotefoundation.org/sites/default/files/TheMyth_of_Secure_Blockchain_Voting.pdf [Google Scholar] [Crossref]

12. March, J. G., & Olsen, J. P. (1984). The new institutionalism: Organizational factors in political life. American Political Science Review, 78(3), 734–749. https://doi.org/10.2307/1961840 [Google Scholar] [Crossref]

13. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Bitcoin.org. https://bitcoin.org/bitcoin.pdf [Google Scholar] [Crossref]

14. Norris, P. (2014). Why electoral integrity matters. Cambridge University Press. https://doi.org/10.1017/CBO9781107280861 [Google Scholar] [Crossref]

15. Specter, M. A., Koppel, J., & Weitzner, D. (2020, August). The ballot is busted before the blockchain: A security analysis of Voatz, the first internet voting application used in US federal elections. Proceedings of the 29th USENIX Security Symposium, 1535–1553. https://doi.org/10.1145/3386554 [Google Scholar] [Crossref]

16. Vinnakota, R. (2021, January 22). Which countries are casting votes using blockchain? HackerNoon. https://hackernoon.com/which-countries-are-casting-votes-using-blockchain-o85b3yh4 [Google Scholar] [Crossref]

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