Secure Cloud AI: Leveraging Artificial Intelligence to Safeguard Cloud Data Sharing Against Fault Injection Attacks

As cloud computing continues to grow, so do the security challenges associate with it. One of the most pressing threats is the fault injection attack, where attackers intentionally introduce faults into a system to disrupt operations or steal sensitive data. This research study presents a comprehensive framework for secure cloud data sharing that combines advanced encryption techniques with Machine Learning (ML) to detect and mitigate fault injection attacks. By leveraging real-time anomaly detection, behavioral analysis, and fault tolerance mechanisms, the proposed system ensures the integrity and confidentiality of shared data. The integration of federated learning and adversarial training further enhances the system's ability to adapt to evolving threats. Experimental results demonstrate the effectiveness of the framework in identifying and neutralizing fault injection attacks, making it a robust solution for modern cloud environments.