Research Article

BMFA: A Blockchain Framework for Secure and Scalable Multifactor Authentication

Authors

  • Asheshemi Nelson Oghenekevwe Department of Computer Science, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria https://orcid.org/0009-0005-9281-198X

    nelson8life@gmail.com

  • Okoro Akpohrobaro Daniel Department of Computer Science, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria
  • Ayeh Blessing Elohor Department of Computer Science, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria
  • Ayo Michael Ifioko Department of Computer Science, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria
  • Atuduhor oghenerukevwe Regha Department of Computer Science, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria

Abstract

This paper introduces a Blockchain-based Multifactor Authentication (BMFA) layering which would enrich data privacy, confidentiality and security of digital systems. The presented framework merges blockchain, its decentralised and immutable ledger and multifactor authentication, which embraces the combination of possession, knowledge, inherence, and behavioural factors. With asymmetric cryptography and smart contracts, the framework provides tamper-resistant, scalable, and auditable processes of authentication. Through computational simulations in this paper, it is revealed that the BMFA framework is much more efficient than the traditional multifactor authentication (TMFA) systems. The most significant results are that the authentication token entropy increased by 45 per cent, tolerance probability against the adversary went down by 60 per cent, and the mean authentication latency is 30 milliseconds, which is still within the bounds of practical use. Moreover, statistical analysis also indicates that the BMFA framework enhances authentication token randomness and reduces the dependencies between two authentication events, thus helping alleviate token prediction and replay attacks. The scalability evaluation reveals that optimised blockchain designs enable the BMFA system to handle growing levels of users without affecting the performance. Altogether, this study confirms the practicality of using a combination of blockchain technology and multifactor authentication to establish an efficient, secure, and reliable structure that can help to overcome modern complexity in a digital context in regard to cybersecurity.

Keywords:

Blockchain Confidentiality Distributed Ledger Multifactor Authentication Privacy Shannon Entropy Smart Contract

Article information

Journal

Scientific Journal of Engineering, and Technology

Volume (Issue)

2(2), (2025)

Pages

134-140

Published

30-10-2025

How to Cite

Asheshemi, N. O., Okoro, A. D., Ayeh, B. E., Ayo, M. I., & Atuduhor, oghenerukevwe R. (2025). BMFA: A Blockchain Framework for Secure and Scalable Multifactor Authentication. Scientific Journal of Engineering, and Technology, 2(2), 134-140. https://doi.org/10.69739/sjet.v2i2.1101

References

Alabdulatif, A., Khalil, I., Yi, X., Alazab, M., & Guizani, M. (2025). Blockchain-based privacy-preserving authentication and access control model for e-health users. Information, 16(3), 219. DOI: https://doi.org/10.3390/info16030219

Ali, A. S. M., Ali, S., Ziaullah, K., Joo, M. I., & Kim, H. C. (2025). IoMT and Blockchain Synergy: A Novel Approach to Health Data Validation and Storage. IEEE Access.

Almadani, M. S., Alotaibi, S., Alsobhi, H., Hussain, O. K., & Hussain, F. K. (2023). Blockchain-based multi-factor authentication: A systematic literature review. Internet of Things, 23, 100844. DOI: https://doi.org/10.1016/j.iot.2023.100844

Alzhrani, F. E., Saeedi, K. A., & Zhao, L. (2022). A taxonomy for characterizing blockchain systems. IEEE Access, 10, 110568-110589. DOI: https://doi.org/10.1109/ACCESS.2022.3214837

Barcelo, A., Queralt, A., & Cortes, T. (2022). Revisiting active object stores: Bringing data locality to the limit with NVM. Future Generation Computer Systems, 129, 425-439. DOI: https://doi.org/10.1016/j.future.2021.10.025

Cheng, G., Chen, Y., Deng, S., Gao, H., & Yin, J. (2021). A blockchain-based mutual authentication scheme for collaborative edge computing. IEEE Transactions on Computational Social Systems, 9(1), 146-158. DOI: https://doi.org/10.1109/TCSS.2021.3056540

Conti, M., Kumar, S., Lal, C., & Ruj, S. (2018). A survey on security and privacy issues of Bitcoin. IEEE Communications Surveys & Tutorials, 20(4), 3416–3452. DOI: https://doi.org/10.1109/COMST.2018.2842460

Cunha, T. B. D., & Manjappa, K. (2024). Private and consortium blockchain-based authentication protocol for IoT devices using PUF. Journal of Communications and Networks, 26(2), 166-181. DOI: https://doi.org/10.23919/JCN.2024.000014

Esposito, C., Ficco, M., & Gupta, B. B. (2021). Blockchain-based authentication and authorization for smart city applications. Information Processing & Management, 58(2), 102468. DOI: https://doi.org/10.1016/j.ipm.2020.102468

Gajmal, Y. M., & Udayakumar, R. (2021). Blockchain-based access control and data sharing mechanism in cloud decentralized storage system. Journal of web engineering, 20(5), 1359-1388. DOI: https://doi.org/10.13052/jwe1540-9589.2054

Issa, W., Moustafa, N., Turnbull, B., Sohrabi, N., & Tari, Z. (2023). Blockchain-based federated learning for securing internet of things: A comprehensive survey. ACM Computing Surveys, 55(9), 1-43. DOI: https://doi.org/10.1145/3560816

Khan, U. H., Khan, Q., Khan, L., Alam, W., Ali, N., Khan, I., ... & Khan, R. A. (2021). MPPT control paradigms for PMSG-WECS: A synergistic control strategy with gain-scheduled sliding mode observer. IEEE Access, 9, 139876-139887. DOI: https://doi.org/10.1109/ACCESS.2021.3119213

Lam, K. Y., Mitra, S., Gondesen, F., & Yi, X. (2021). ANT-centric IoT security reference architecture—Security-by-design for satellite-enabled smart cities. IEEE Internet of Things Journal, 9(8), 5895-5908. DOI: https://doi.org/10.1109/JIOT.2021.3073734

Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2020). A survey on the security of blockchain systems. Future Generation Computer Systems, 107, 841–853. DOI: https://doi.org/10.1016/j.future.2017.08.020

Narayanan, A., Bonneau, J., Felten, E., Miller, A., & Goldfeder, S. (2016). Bitcoin and cryptocurrency technologies: A comprehensive introduction.

Nasrinasrabadi, M., A Hejazi, M., Chaharmahali, E., & Hussein, M. (2024). A Comprehensive Review of Blockchain Integration in Smart Grid with a Special Focus on Internet of Things. Ehsan and Hussein, Mousa, A Comprehensive Review of Blockchain Integration in Smart Grid with a Special Focus on Internet of Things (August 10, 2024). DOI: https://doi.org/10.2139/ssrn.5237919

Nosenko, A., Cheng, Y., & Chen, H. (2023). Password and passphrase guessing with recurrent neural networks. Information systems frontiers, 25(2), 549-565. DOI: https://doi.org/10.1007/s10796-022-10325-x

Oduselu-Hassan, O. E. (2025). A Second-Order Imex-Rk Approach for Energy-Stable Phase Field Crystal Simulations. Asian Basic and Applied Research Journal, 7(1), 193-202. DOI: https://doi.org/10.56557/abaarj/2025/v7i1166

Oduselu-Hassan, O. E., & Kenneth, O. (2024). Synergies between Machine Learning, Artificial Intelligence, and Game Theory for Complex Decision-Making. Artificial Intelligence, and Game Theory for Complex Decision-Making (November 15, 2024). Asian Research Journal of Mathematics, 20(11), 10-9734 DOI: https://doi.org/10.9734/arjom/2024/v20i11863

Oktian, Y. E., & Lee, S. G. (2020). BorderChain: Blockchain-based access control framework for the Internet of Things endpoint. IEEE Access, 9, 3592-3615.

Oktian, Y. E., & Lee, S. G. (2020). BorderChain: Blockchain-based access control framework for the Internet of Things endpoint. IEEE Access, 9, 3592–3615. DOI: https://doi.org/10.1109/ACCESS.2020.3047413

Oladayo, O. H. (2025). Advancing Hybrid Numerical Methods for Nonlinear Stochastic Differential Equations: Applications in Complex Systems. Asian Journal of Research in Computer Science, 18(1), 124-132. DOI: https://doi.org/10.9734/ajrcos/2025/v18i1553

Rahman, A., Kundu, D., Debnath, T., Rahman, M., & Islam, M. J. (2024). Blockchain-based AI Methods for Managing Industrial IoT: Recent Developments, Integration Challenges and Opportunities. arXiv preprint arXiv:2405.12550.

Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379–423. DOI: https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

Sharma, P., Jindal, R., & Borah, M. D. (2021). Blockchain-based decentralized architecture for cloud storage system. Journal of Information Security and Applications, 62, 102970. DOI: https://doi.org/10.1016/j.jisa.2021.102970

Sousa, J., Bessani, A., & Vukolic, M. (2018). A Byzantine fault-tolerant ordering service for the Hyperledger Fabric blockchain platform. 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 51–58. DOI: https://doi.org/10.1109/DSN.2018.00018

Tran, L., Nguyen, T., Seo, C., Kim, H., & Choi, D. (2022). A Survey on Password Guessing. arXiv preprint arXiv:2212.08796.

Wang, W., Hoang, D. T., Hu, P., Xiong, Z., Niyato, D., Wang, P., Wen, Y., & Kim, D. I. (2019). A survey on consensus mechanisms and mining strategies in blockchain. IEEE Access, 7, 22328–22370. DOI: https://doi.org/10.1109/ACCESS.2019.2896108

Zhai, P., He, J., & Zhu, N. (2022). Blockchain-based Internet of Things access control technology in intelligent manufacturing. Applied Sciences, 12(7), 3692. DOI: https://doi.org/10.3390/app12073692

Downloads

Views

0

Downloads

0