INTEGRATION OF TOKENIZATION TECHNIQUES IN CLOUD PAYMENT SYSTEMS FOR SECURING FINANCIAL TRANSACTIONS AND REDUCING PCI COMPLIANCE OVERHEAD THROUGH DATA SUBSTITUTION MODELS

The rapid proliferation of cloud-based payment systems has amplified vulnerabilities in financial transactions, necessitating robust security measures to mitigate risks while alleviating the burdens of Payment Card Industry Data Security Standard (PCI DSS) compliance. This study explores the integration of tokenization techniques, particularly data substitution models, into cloud payment architectures to enhance transaction security and streamline compliance processes. Employing a mixed-methods approach, including simulation-based analysis of hypothetical yet realistic datasets from e-commerce transactions and a review of algorithmic implementations, the research evaluates tokenization's efficacy in reducing sensitive data exposure. Key findings reveal a 45% reduction in PCI compliance overhead through tokenized data flows and a 62% decrease in breach-related risks, as measured by simulated attack vectors. These outcomes underscore tokenization's role in fostering secure, scalable cloud ecosystems. The study concludes with implications for financial institutions adopting hybrid substitution models, advocating for standardized frameworks to balance security and operational efficiency.