An Intelligent Cybersecurity Framework for Data Protection in Cloud Computing Environments

Abstract

Cloud computing offers flexible and scalable infrastructure, platforms, and applications; but, its shared, programmable, and distributed framework introduces interconnected threats to sensitive information. This research formulates ICF-CloudSecure, a sophisticated, data-oriented cybersecurity architecture that incorporates multifactor authentication, identity and access management, cryptographic safeguards, AI-driven threat analysis, machine learning-based intrusion detection, ongoing risk assessment, and automated incident management. The study employs a design-science approach that includes threat modeling, security requirements engineering, modular architecture creation, feature pipeline specification, risk assessment, and analytical validation via requirements-to-control traceability and failure scenario evaluation. Multisource cloud telemetry is standardized, and features related to identity, network, workload, data access, and time are derived. Supervised and anomaly-detection methods subsequently produce calibrated evidence instead of independent enforcement determinations. A constrained risk engine integrates threat intelligence, vulnerability exposure, asset significance, data sensitivity, contextual irregularities, and validated mitigating measures to trigger policy-driven, least-privilege actions. The design-level assessment illustrates traceability across objectives of confidentiality, integrity, availability, scalability, dependability, threat detection, and privacy via preventative, detective, responsive, and evidentiary measures. Architecture delineates inference from enforcement, facilitates reversible response protocols, and maintains human oversight, auditability, and multi-cloud adaptability. A validation methodology that may be replicated includes datasets that are segregated by tenant and time, cross-dataset evaluations, ablation experiments, calibration assessments, robustness evaluations, and operational metrics are also delineated. ICF-CloudSecure thus offers a verifiable basis for intelligent and responsible cloud data safeguarding.

Keywords: Cloud Security; Data Protection; Artificial Intelligence; Machine Learning; Intrusion Detection; Zero Trust; Automated Incident Response