Data Encryption Strategies for Securing Financial Transactions in Cloud Data Warehouses
DOI:
https://doi.org/10.63282/3050-9246/ICRTCSIT-101Keywords:
Data Encryption, Cloud Security, Virtualization, Cloud Data Warehouses, U.S. Banking Compliance, Secure Financial TransactionsAbstract
The adoption of cloud data warehouses has transformed the financial services industry in the United States, enabling banks to process and analyze petabytes of transactional data in near real time. However, this shift also introduces significant risks related to confidentiality, integrity, and availability of sensitive financial data. Encryption—both at rest and in transit—remains a cornerstone of secure architecture, while virtualization adds an additional layer of protection by isolating workloads and enabling trusted execution environments. This paper presents an in-depth analysis of data encryption strategies specifically tailored for U.S. banks leveraging cloud warehouses such as Amazon Redshift, Snowflake, and Google BigQuery. We examine regulatory drivers including the Gramm-Leach-Bliley Act (GLBA), Federal Financial Institutions Examination Council (FFIEC) guidelines, and PCI DSS standards, and map them to encryption requirements. Our findings integrate theoretical insights with practical results from a case study involving a U.S. commercial bank migrating its Teradata warehouse to Snowflake on AWS. Experimental results demonstrate that encryption overheads remain within acceptable limits (<7% latency increase), while virtualization-based trusted execution environments (Intel SGX enclaves) secure fraud detection models with negligible leakage risk. We argue that the combination of encryption and virtualization forms a dual-pillar strategy for ensuring resilient, compliant, and confidential processing of financial transactions in cloud data warehouses
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