Generative AI for Real-Time Cloud Security: Advanced Anomaly Detection Using GPT Models

Cloud computing has become the backbone of modern digital infrastructure, enabling scalable and flexible services for organizations worldwide. However, the rapid growth of cloud environments has also introduced significant security challenges such as unauthorized access, data breaches, and sophisticated cyberattacks. Traditional security systems rely on rule-based detection mechanisms that often fail to identify unknown threats. This paper proposes a Generative Artificial Intelligence based framework for real-time cloud security monitoring. The proposed system utilizes advanced generative models to analyse cloud logs, network traffic, and user behaviour to identify abnormal patterns that may indicate potential security threats. By leveraging deep learning and generative AI capabilities, the system improves the accuracy and speed of anomaly detection. The proposed approach enhances cloud security by providing intelligent threat detection and real-time monitoring capabilities.