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Abstract
Cloud computing has transformed data storage by allowing it to scale and be affordable, but ongoing security issues like data breaches, integrity attacks, and compliance loopholes continue to pose key concerns. This research systematically examines more than 50 scholarly papers to analyze security measures in cloud computing. A hybrid architecture is proposed that combines post-quantum-resistant encryption to protect against future cryptographic attacks, blockchain-based auditing for secure and unalterable data integrity proof, and anomaly detection via AI to increase real-time threat detection. Simulated experimentation shows a 40% decrease in unauthorized access events and a 30% quicker audit response time over conventional approaches. The study also offers actionable insights for cloud service providers (CSPs) and businesses, prioritizing adaptive threat detection systems and standardized regulatory protocols. Future research directions include the development of decentralized audit frameworks, improving AI/ML security models, and harmonizing global compliance standards to meet emerging threats in cloud environments.
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