Implementing Secure Cloud Storage policies with Blockchain and AI

Cloud computing has become a vital infrastructure for storing and accessing data remotely. However, this centralized model introduces significant security and privacy concerns, including data breaches, insider threats, and regulatory non-compliance. To address these issues, this paper presents a hybrid framework that integrates Blockchain and Artificial Intelligence (AI) to implement a secure cloud storage policy. Blockchain provides immutability, transparency, and decentralized data access management, reducing risks associated with tampering and unauthorized modifications. Concurrently, AI enhances threat detection through real-time anomaly identification and predictive analytics, allowing proactive response mechanisms to potential security breaches. The proposed architecture combines smart contracts for automated policy enforcement with AI modules that analyse access behaviours and assign risk scores to cloud storage activities. Case studies in healthcare and finance demonstrate the effectiveness of the framework, highlighting increased data integrity, regulatory compliance, and reduced incidents of insider threats and fraudulent activities. The paper also explores technical challenges such as Blockchain scalability, data privacy in public ledgers, and AI model biases. It proposes future advancements, including federated learning, edge AI deployment, and the development of quantum-resistant Blockchain algorithms to further enhance system robustness. This interdisciplinary approach illustrates that the synergy between Blockchain and AI can address modern cloud security needs by creating intelligent, adaptive, and secure data environments. Through continuous learning and decentralized control, such a framework enables organizations to meet growing cybersecurity demands while maintaining operational agility and user trust