ZERO-TRUST ARCHITECTURE IN ETL PIPELINES ENSURING DATA SECURITY IN MULTI-CLOUD ENVIRONMENTS

Abstract

The increasing reliance on multi-cloud environments for data integration and processing has exposed significant vulnerabilities in traditional Extract, Transform, and Load (ETL) pipelines. This approach isn't equipped to handle the security challenges of moving data across varied and widespread networks. The typical systems today don't have strong enough security features to protect data as it moves through the intricate paths of distributed networks. The research faces these obstacles head-on and presents a groundbreaking solution, the Zero-Trust ETL Pipeline or ZTEP framework. It uniquely blends Zero-Trust Architecture principles within ETL workflows. Embodying the principle of "never trust, always verify," the framework of ZTEP strongly focuses on confirming identities, implementing detailed access permissions, securing data through encryption from start to finish, and leveraging AI and machine learning to spot unusual activities immediately. In addressing the specific security hurdles by using multiple cloud platforms—such as uneven access management, weak points in how APIs interact, and a broader area for potential cyber-attacks—the suggested framework steps in with solutions. It brings to the table a set of core components: a logging system built on blockchain technology to ensure that audit trails are tamper-proof; a flexible approach to enforcing rules that aim to reduce the risk from those within the organization, and a design that can be adjusted or expanded easily, improving both the scale at which it can operate and the efficiency with which it does so. The ZTEP framework weaves in top-notch security features to safeguard data at every stage of the ETL pipeline. This approach majorly scales down the chance of data getting exposed or tampered with due to unauthorized entry or breaches. Testing in a setup that mimicked a multi-cloud scenario confirmed the strength of the ZTEP framework. It showed a notable decrease in attempts to gain unauthorized access by 80% and proved its efficacy in spotting anomalies as they happen with a 95% accuracy rate. Furthermore, by weaving in cloud-native instruments like AWS Identity and Access Management alongside Kubernetes, the structure's efficiency got a boost, allowing it to scale up while still keeping a tight lid on security matters. Findings from the case study highlight how ZTEP stands out as a game-changing approach for safely merging data within today's digital landscapes. This study bridges an essential void in current academic discussions by exploring the application of ZTA principles within ETL pipelines. It lays out a path for entities to strengthen their data engineering strategies. The forthcoming inquiries will delve into how the incorporation of quantum-resistant cryptography, along with hybrid cloud compatibility and streamlined policy automation, can significantly boost the robustness and flexibility of the framework.