Authors: Ravi C. Menon
Abstract: Cloud computing’s global adoption has revolutionized data management, but it has also intensified concerns regarding data confidentiality and security. Traditional encryption models, characterized by static configurations and fixed cryptographic policies, struggle to address the dynamic threat landscape of modern cloud environments. This review examines the impact of adaptive encryption algorithms—intelligent, context-aware mechanisms capable of dynamically modifying encryption parameters based on real-time risk assessments—on enhancing cloud data confidentiality.The paper explores the architectural principles, operational dynamics, and technological enablers of adaptive encryption, emphasizing its integration with AI-driven analytics, blockchain-based key management, and quantum-resistant cryptography. By analyzing its applications across multi-cloud, hybrid, and edge infrastructures, the review demonstrates how adaptive encryption fosters continuous, context-sensitive data protection.Despite its advantages, adaptive encryption also faces challenges including computational overhead, algorithm transparency, and interoperability across heterogeneous cloud environments. Addressing these barriers requires a balance between automation, explainability, and governance to ensure sustainable adoption. The study concludes that adaptive encryption signifies a pivotal evolution in cloud security—transforming static encryption models into self-learning, resilient, and proactive defense systems capable of anticipating and countering emerging threats.
DOI: http://doi.org/10.5281/zenodo.17800103
