Secure Data Migration in Multi-Cloud Systems Using AI and Blockchain

Abstract

The rapid adoption of multi-cloud environments has led to increased complexities in data migration processes, necessitating robust solutions to ensure data security and integrity. This paper presents a novel approach for secure data migration in multi-cloud systems by leveraging the synergistic capabilities of Artificial Intelligence (AI) and Blockchain technology. The proposed framework employs AI algorithms to assess data sensitivity, optimize migration strategies, and predict potential security vulnerabilities during data transfers. Simultaneously, Blockchain is utilized to create a tamper-proof audit trail of all migration activities, enhancing transparency and accountability. By combining AI's predictive analytics with Blockchain's immutable record-keeping, our solution addresses common challenges such as data breaches, unauthorized access, and compliance with regulatory standards like GDPR and HIPAA. Through a series of experiments conducted in simulated multi-cloud environments, we demonstrate the effectiveness of our approach in mitigating risks associated with data migration while maintaining high levels of performance. The results indicate a significant reduction in security incidents and improved efficiency in data handling processes. This study contributes to the growing body of knowledge on secure cloud computing practices and offers practical insights for organizations seeking to enhance the security of their multi-cloud data migration operations.