The week's pick
Random Articles
Reseach Article
PINAF: A Multi-Level Security Model for Mobile Payment Systems in Nigeria
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 17 |
| Year of Publication: 2025 |
| Authors: Mobolaji F. Oladapo, Olutayo K. Boyinbode, Kolawole G. Akintola |
10.5120/ijca2025925086
|
Mobolaji F. Oladapo, Olutayo K. Boyinbode, Kolawole G. Akintola . PINAF: A Multi-Level Security Model for Mobile Payment Systems in Nigeria. International Journal of Computer Applications. 187, 17 ( Jun 2025), 1-7. DOI=10.5120/ijca2025925086
Abstract
Mobile payment systems face significant trust challenges within the Nigerian population, stemming from perceived risks, system complexity, and concerns about reliability. In response, the 2011 Cashless Policy enacted by the Central Bank of Nigeria (CBN) has continued to drive the development of safer and more user-friendly mobile payment platforms. Common security mechanisms include personal identification numbers (PINs), biometric verification, and facial recognition. Integrating these modes provides enhanced security and addresses key gaps in Nigeria’s cybersecurity landscape. This research presents the development of a multi-level security model for mobile payment systems, named PINAF, designed to address these challenges. The PINAF application encompasses user enrollment, authentication, and payment processing. Face detection was implemented using the Viola-Jones algorithm, facial recognition was performed using a Support Vector Machine (SVM), and user data was encrypted using the Rivest-Shamir-Adleman (RSA) algorithm. Evaluation results showed that the Viola-Jones + SVM approach achieved 90% accuracy, 92.3% recall, and an F1-score of 0.90, outperforming existing facial recognition models. The proposed model demonstrates a significant improvement in the security and reliability of mobile payment systems in Nigeria.
References
- Olayinka Abolade. Consumers’ perception towards Fintech and Traditional Financial Institutions (A case study of Nigeria). PhD thesis, Dublin, National College of Ireland, 2023.
- Ikechukwu A Acha, Clementina Kanu, and Godswill A Agu. Cashless policy in nigeria: The mechanics, benefits and problems. Innovative Journal of Economics and Financial Studies, 1(1):28–38, 2017.
- Waqas Ahmed, Aamir Rasool, Abdul Rehman Javed, Neeraj Kumar, Thippa Reddy Gadekallu, Zunera Jalil, and Natalia Kryvinska. Security in next generation mobile payment systems: A comprehensive survey. IEEE Access, 9:115932– 115950, 2021.
- Angelo Galiano, Alessandro Massaro, Donato Barbuzzi, Mattia Legrottaglie, Valeria Vitti, Leonardo Pellicani, and Vitangelo Birardi. Face recognition system on mobile device based on web service approach. Int. J. Comput. Sci. Inf. Technol.( IJCSIT), 7(4):2130–2135, 2016.
- Marti A. Hearst, Susan T Dumais, Edgar Osuna, John Platt, and Bernhard Scholkopf. Support vector machines. IEEE Intelligent Systems and their applications, 13(4):18–28, 1998.
- Odi Nwankwo and Onyekachi Richard Eze. Electronic payment in cashless economy of nigeria: Problems and prospect. Journal of Management Research, 5(1), 2013.
- Echekoba Felix Nwaolisa and Ezu Gideon Kasie. Electronic retail payment systems: User acceptability and payment problems in nigeria. Arabian Journal of Business and Management Review, 34(953):1–18, 2012.
- Ronald L Rivest, Adi Shamir, and Leonard Adleman. A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2):120–126, 1978.
- Alaa Mahdi Sahi, Haliyana Khalid, Alhamzah F Abbas, Khaled Zedan, Saleh FA Khatib, and Hamzeh Al Amosh. The research trend of security and privacy in digital payment. In Informatics, volume 9, page 32. MDPI, 2022.
- Paul Viola and Michael Jones. Rapid object detection using a boosted cascade of simple features. In Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition. CVPR 2001, volume 1, pages I–I. Ieee, 2001.
Index Terms
Keywords