Fully Homomorphic Encryption: Revolutionizing Payment Security

Authors

  • Hirenkumar Patel Mastercard Inc, USA Author

DOI:

https://doi.org/10.32628/CSEIT25112706

Keywords:

Homomorphic Encryption, Payment Security, Tokenization, Card-Not-Present Fraud, Privacy-Preserving Computation

Abstract

with legacy systems, performance overhead, standardization requirements, and interoperability concerns across heterogeneous payment ecosystems. This article analyzes these challenges alongside emerging optimization techniques and implementation strategies that show promise for overcoming current adoption barriers. As computational efficiency continues to improve through hardware acceleration and algorithmic innovations, FHE stands poised to revolutionize payment security by fundamentally altering how sensitive financial data is processed in distributed environments.

Downloads

Download data is not yet available.

References

D. Chandravathi, et al, “Performance Analysis of Homomorphic Encryption algorithms for Cloud Data Security,” 2018, Available: https://www.researchgate.net/publication/344845183_Performance_Analysis_of_Homomorphic_Encryption_algorithms_for_Cloud_Data_Security

Omolara Patricia Olaiya, et al, “Encryption techniques for financial data security in fintech applications,” 2024, Available: https://www.researchgate.net/profile/Omolara-Olaiya/publication/382023338_Encryption_techniques_for_financial_data_security_in_fintech_applications/links/668837a90a25e27fbc2b92b6/Encryption-techniques-for-financial-data-security-in-fintech-applications.pdf

Yerra, S. (2023). Leveraging Python and machine learning for anomaly detection in order tracking systems. doi : https://doi.org/10.32628/CSEIT2311354

J. Jangid, "Secure microservice communication in optical networks," Journal of Information Systems Engineering and Management, vol. 10, no. 21s, 2025. doi: 10.52783/jisem.v10i21s.3455

Dan Mitrea, et al, “Smart contracts and homomorphic encryption for private P2P energy trading and demand response on blockchain,” 2023, Available: https://www.sciencedirect.com/science/article/pii/S2405844023095658

Mebiratu Beyene, et al, “Performance Analysis of Homomorphic Cryptosystem on Data Security in Cloud Computing,” 2019, Available: https://www.researchgate.net/publication/338365736_Performance_Analysis_of_Homomorphic_Cryptosystem_on_Data_Security_in_Cloud_Computing

Li, et al, “Privacy preserving via multi-key homomorphic encryption in cloud computing,” 2023, Available: https://www.sciencedirect.com/science/article/abs/pii/S2214212623000479

Alex Sangers, et al, “Secure Multiparty PageRank Algorithm for Collaborative Fraud Detection,” 2019, Available: https://www.researchgate.net/publication/336420703_Secure_Multiparty_PageRank_Algorithm_for_Collaborative_Fraud_Detection

Chris Gilbert, et al, “The Effectiveness of Homomorphic Encryption in Protecting Data Privacy,” 2024, Available: https://www.researchgate.net/publication/385818007_The_Effectiveness_of_Homomorphic_Encryption_in_Protecting_Data_Privacy

Md Rafiqul Islam. Et al, “Cryptocurrency Integration Challenges in Blockchain for Financial Institution,” 2023, Available: https://www.researchgate.net/publication/368208525_Cryptocurrency_Integration_Challenges_in_blockchain_for_Financial_Institutions

Finney Daniel Shadrach, et al, “Challenges and Opportunities Associated with Homomorphic Encryption for Financial Cryptography,” 2023, Available: https://www.researchgate.net/publication/372790090_Challenges_and_Opportunities_Associated_with_Homomorphic_Encryption_for_Financial_Cryptography

Downloads

Published

26-03-2025

Issue

Section

Research Articles