Adaptive Architecture for Secure Digital Payments
DOI:
https://doi.org/10.32628/IJSRSET25121157Keywords:
Smart Payment Security, Inclusive Digital Finance, Insider Threat Mitigation, Multi-Factor Authentication, Post-Quantum Cryptography, Zero Trust Architecture, Usability and Accessibility in FinTechAbstract
The expansion of digital payment technologies has ushered in transformative benefits for global commerce but has also introduced complex security, usability, and regulatory challenges. This research builds upon existing security frameworks by addressing significant gaps in real-world implementation, inclusive design, quantum readiness, and policy adaptation. Through a multi-dimensional analysis, the study investigates the disconnect between theoretical frameworks and production-scale deployments, especially in diverse market environments with infrastructure constraints. It emphasizes the importance of human-centered design in authentication systems, explores insider threat mitigation strategies, and introduces proactive security models including role-based controls and Zero Trust Architecture. Finally, the paper offers actionable strategies for scaling secure digital payment infrastructures while maintaining usability, compliance, and future-proofing against emerging technological risks. The findings aim to guide software developers, financial institutions, and policymakers in building resilient, inclusive, and regulation-aware payment systems for the next decade.
Downloads
References
Apon, D., Dang, Q., & Perlner, R. (2023). Implementing post-quantum cryptography in payment networks: Challenges and solutions. Journal of Cybersecurity, 9(1).
Bailey, K. O., Okolica, J. S., & Peterson, G. L. (2021). User re-authentication via behavioral biometrics in mobile payment applications. Computers & Security.
Saqib, M., Malhotra, S., Mehta, D., Jangid, J., Yashu, F., & Dixit, S. (2025). Optimizing spot instance reliability and security using cloud-native data and tools. Journal of Information Systems Engineering and Management, 10(14s), 720–731. https://doi.org/10.52783/jisem.v10i14s.2387
Zhang, Y., Li, X., & Wang, H. (2023). Secure middleware for hybrid banking architectures: A case study of payment system migration. Journal of Systems and Software.
Jangid, J. (2020). Efficient training data caching for deep learning in edge computing networks. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 7(5), 337–362. https://doi.org/10.32628/CSEIT20631113
Ngai, E. W. T., & Hu, Y. (2023). Deep learning for real-time payment fraud detection: An empirical comparison of architectures. Decision Support Systems.
Venkata, B. (2020). SMART PAYMENT SECURITY: A SOFTWARE DEVELOPER’S ROLE IN PREVENTING FRAUD AND DATA BREACHES.
Dixit, S., & Jangid, J. (2024). Asynchronous SCIM profile for security event tokens. Journal of Computational Analysis and Applications, 33(6), 1357–1371. https://eudoxuspress.com/index.php/pub/article/view/1935
Malik, S., & Rao, A. (2023). Adaptive security models for mobile money in low-connectivity regions. Information Systems Frontiers, 25(2), 743-760.
Golla, M., & Dürmuth, M. (2022). Biometric multi-factor authentication: On the usability of the FingerPIN scheme. Security and Privacy.
Mohurle, S., & Patil, D. (2023). Self-healing payment systems: Automated vulnerability patching in production environments. Automated Software Engineering, 30(1), 1-30.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Journal of Scientific Research in Science, Engineering and Technology

This work is licensed under a Creative Commons Attribution 4.0 International License.