Cloud-Native Anonymization Framework for Secure Data Migration: A Technical Deep Dive
ABSTRACT: Cloud-native anonymization frameworks represent a transformative shift in how organizations protect sensitive data during cloud migration. As enterprises increasingly adopt cloud technologies, the need for robust data protection mechanisms has become paramount. These frameworks leverage advanced capabilities including machine learning, automated pattern recognition, and real-time processing to ensure data privacy while maintaining utility. By integrating containerization, microservices architecture, and automated scaling, organizations can achieve comprehensive data protection throughout their migration journey. The combination of sophisticated anonymization techniques with cloud-native principles enables organizations to meet stringent compliance requirements while optimizing operational efficiency and reducing security risks.
Institutions
- Fugro (Norway) (NO)
Publication Details
- Journal
- International journal of multidisciplinary and scientific emerging research.
- Published
- 2025-02-20
- DOI
- https://doi.org/10.15662/ijmserh.2025.1302001
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.00