This work focuses on the security of mobile payments in Internet of Things networks, with particular emphasis on the integration of post-quantum cryptographic principles. The study adopts a modeling and simulation-based approach to analyze security challenges arising from the advent of quantum computing. The main contributions include an analytical review of post-quantum cryptographic algorithms, the identification of potential vulnerabilities in IoT-based mobile payment systems, and the development of a multivariate mathematical framework to evaluate security-performance trade-offs. Through synthetic data generation and statistical modeling, the proposed framework highlights the impact of cryptographic complexity, network latency, and device resource constraints on transaction security. The results demonstrate how post-quantum-aware security mechanisms can be optimized under practical IoT constraints. The significance of this work lies in its proactive approach to long-term security, addressing the growing vulnerability of traditional RSA- and ECC-based systems in the presence of quantum adversaries. By focusing on abstraction, modeling, and simulation, this study provides insights that support the design of future quantum-resistant mobile payment architectures in IoT environments.
References
[1]
Statista (2023) Value of Mobile Payments Worldwide from 2017 to 2028.
[2]
MarketsandMarkets (2021) Internet of Things (IoT) Market by Component, Application, and Region—Global Forecast to 2027.
[3]
Deloitte (2022). The State of the Mobile Payments Market.
[4]
Gartner (2023) Gartner Says Global Spending on Information Security Will Reach 172 Dollar Billion in 2022.
[5]
Lentz, J.W. and Johnson, M. (2020) Key Management for Payment Systems: An Overview of DUKPT.
[6]
Grubbs, J.D. (2021) Understanding DUKPT: A Guide for Key Management in Payment Systems.
[7]
National Institute of Standards and Technology (NIST) (2012). NIST Special Publication 800-108: Recommendation for a Key Derivation Function for General Use.
Housley, R. (2009) PKCS # 11 Cryptographic Token Interface Base Specification Version 2.20.
[10]
Günther, S. and Heisel, M. (2018) A Survey on Cryptography Standards for Mobile Payment Solutions.
[11]
Payment Card Industry Security Standards Council (2022) Payment Card Industry Data Security Standard (PCI DSS) Version 4.0.
[12]
Payment Card Industry Security Standards Council (2016) PCI Mobile Payment Acceptance Security Guidelines.
[13]
Feng, C. and Li, J. (2020) Understanding the Impact of Total Quality Management Practices on Electronic Payment Systems. International Journal of Information Management, 50, 80-90.
[14]
Sila, I. and Azaiez, M.N. (2019) Quality in Payment Systems: Framework and Propositions. Journal of Payments Strategy Systems, 13, 20-32.
[15]
Maitra, S., Kundu, S. and Shankar, A. (2024) Real-Time Anomaly Detection Using Convolutional Autoencoder with Dynamic Threshold.
[16]
Mbonigaba, V., Nahayo, F., Moutsinga, O., Okalas-Ossami, D., Nibitanga, R. and Niyonsaba, T. (2024) Modeling and Implementation of a Data Security and Protection Medium Using the Generated Key Based on Electromagnetic Wave Propagation Theories. JournalofComputerandCommunications, 12, 131-140. https://doi.org/10.4236/jcc.2024.129008
[17]
Mbonigaba, V., Nahayo, F., Moutsinga, O. and Dieudonné, O. (2024) Development of a Post Quantum Encryption Key Generation Algorithm Using Electromagnetic Wave Propagation Theory. JournalofInformationSecurity, 15, 53-62. https://doi.org/10.4236/jis.2024.151005
[18]
Zhang, Y. and Lee, K. (2020). Mathematical Optimization Methods for Mobile Payment and IoT Security. IEEE Transactions on Industrial Informatics, 16, 4157-4166.
[19]
Menezes, A.J., Oorschot, P.C. and Vanstone, S.A. (1996). Handbook of Applied Cryptography. CRC Press.