Cloud-Based Data Storage and Security Framework for Enterprise Computing

Abstract

Cloud storage has become a central component of enterprise computing because it offers elastic capacity, location-independent access, rapid provisioning, and lower infrastructure-management overhead. These benefits are accompanied by risks arising from outsourced data custody, multi-tenancy, Internet-facing interfaces, privileged administrator access, key exposure, service outages, and unauthorized disclosure. This methodology paper proposes a layered cloud-based data storage and security framework for enterprise environments that integrates data classification, identity and access management, encryption, centralized key management, integrity verification, monitoring, backup, and disaster recovery. The study is designed as a controlled simulation and prototype evaluation in which a conventional cloud-storage baseline is compared with the proposed secure framework under normal workload and adversarial conditions. Performance is assessed using upload/download throughput, access latency, encryption overhead, unauthorized-access blocking rate, integrity-tamper detection rate, and recovery time. The methodology combines role-based and attribute-aware authorization with AES-256 protection for data at rest, TLS for data in transit, hash-based integrity verification, append-only audit logging, and policy-controlled backup replication. Illustrative results demonstrate the expected trade-off: modest processing overhead in exchange for substantial gains in confidentiality, integrity, accountability, and recoverability. The framework is intended as a reproducible evaluation model rather than a claim of completed enterprise deployment.