NEXT-GEN E-COMMERCE WEBSITE WITH ENCRYPTED PAYMENT GATEWAY USING GENETIC ALGORITHMS

Luxmi; Manik Jain; Meenakshi; Jagriti Malviya

doi:10.29121/ijetmr.v10.i5.2023.1599

NEXT-GEN E-COMMERCE WEBSITE WITH ENCRYPTED PAYMENT GATEWAY USING GENETIC ALGORITHMS

Authors

Luxmi Computer Science and Engineering, Echelon Institute of Technology, Faridabad
Manik Jain Computer Science and Engineering, Echelon Institute of Technology, Faridabad
Meenakshi Computer Science and Engineering, Echelon Institute of Technology, Faridabad
Jagriti Malviya Computer Science and Engineering, Echelon Institute of Technology, Faridabad

DOI:

https://doi.org/10.29121/ijetmr.v10.i5.2023.1599

Keywords:

E-Commerce, Encrypted Payment, Gateway, Genetic Algorithms, Information Technology

Abstract

The rapid advancement of Information Technology (IT) has transformed traditional commerce, especially in the realm of digital payments. The Indian government's push during the demonetization period accelerated the shift from conventional payment systems to secure, convenient digital transactions. The growing penetration of smartphones and internet connectivity has further fueled the adoption of digital payments across urban and rural regions. However, with the increasing reliance on API-driven systems for online transactions, ensuring data security has become paramount. Many platforms still operate on outdated APIs, while newer ones continue to emerge, posing both opportunities and security risks. To address these concerns, this project proposes an E-commerce platform integrated with a secure payment gateway utilizing genetic encryption techniques. Genetic encryption, inspired by the principles of genetic algorithms, introduces an adaptive and robust approach to securing sensitive transactional data and API communications. This system not only enhances payment security but also ensures safe and efficient data exchanges between third-party services, paving the way for a more resilient and trustworthy digital commerce ecosystem.

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References

Global Payments Inc. (2020). Developer's Guide To Payment APIs.

Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley.

Holland, J. H. (1975). Adaptation in Natural and Artificial Systems: An Introductory Analysis With Applications To Biology, Control, and Artificial Intelligence. University of Michigan Press.

Kaufman, C., Perlman, R., & Speciner, M. (2016). Network Security: Private Communication in A Public World (2nd ed.). Prentice Hall.

Liu, J., Zeng, W. (2021). A Survey on Secure APIs in E-Commerce Payment Systems. IEEE Transactions on Services Computing, 14(3), 810-823.

OWASP Foundation. (2021). API Security Top 10. Retrieved from https://owasp.org/www-project-api-security/

Rob, M., Opara, E. (2003). Electronic Commerce. International Thomson Publishing.

Stallings, W. (2017). Cryptography and Network Security: Principles and Practice (7th ed.). Pearson.

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Published

2023-05-30

How to Cite

Luxmi, Jain, M., Meenakshi, & Malviya, J. (2023). NEXT-GEN E-COMMERCE WEBSITE WITH ENCRYPTED PAYMENT GATEWAY USING GENETIC ALGORITHMS. International Journal of Engineering Technologies and Management Research, 10(5), 70–77. https://doi.org/10.29121/ijetmr.v10.i5.2023.1599

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Issue

Vol. 10 No. 5 (2023): IJETMR: Volume 10 Issue 5 - May, 2023

Section

Articles

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