Comparative Study of Data Security Techniques in Distributed Cloud Environments

Abstract

Distributed cloud environments improve availability, elasticity, and geographic reach by placing data and services across multiple cloud nodes, but distribution also enlarges the attack surface and complicates confidentiality, integrity, access control, key management, and accountability. This methodology paper develops a structured comparative framework for data-security techniques that were available in the literature up to 2017. The study compares conventional encryption with managed keys, attribute-based encryption (ABE), provable data possession and privacy-preserving public auditing, message-locked/convergent encryption for deduplication, and hybrid-cloud authorized deduplication. The comparison uses six criteria: confidentiality strength, integrity assurance, fine-grained access control, scalability across distributed nodes, computational overhead, and communication/storage overhead. A weighted analytical scoring method is used so that heterogeneous techniques can be assessed consistently without claiming unreported experimental measurements. The analysis shows that no single technique satisfies all security and efficiency objectives. Symmetric encryption remains highly efficient for bulk confidentiality, ABE offers superior policy-driven access control at higher computational cost, auditing mechanisms strengthen integrity without replacing encryption, and deduplication-aware cryptography reduces storage cost but introduces distinct leakage and key-management concerns. A layered architecture combining efficient encryption, distributed policy/key control, independent integrity verification, and authorization-aware deduplication provides the most balanced security posture for distributed cloud deployments.