Optimizing Cloud Security with Autonomous AI-Driven Defence Mechanisms

Abstract

Maintaining strong security has become increasingly difficult as a result of cloud computing's quick growth, especially when it comes to identifying and countering sophisticated cyberattacks. In cloud environments, automated threat intelligence and response through the use of AI-driven algorithms is the main emphasis of this research. Cloud infrastructure protection has historically relied on traditional security techniques like Rule-Based Systems, Behavioural Analysis, and Signature-Based Detection, but these methods frequently fall behind the constantly changing threat landscape. Real-time threat management can be inefficient due to these systems' reactive nature, limited capacity to identify emerging threats, and potential resource consumption.The suggested method offers a sophisticated AI-driven paradigm that combines Federated Learning (FL), Reinforcement Learning (RL), and Deep Learning for improved cloud security. Reinforcement learning gives the system the ability to automatically adjust and improve its threat response tactics, while deep learning gives it the ability to identify intricate patterns and anomalies that conventional approaches could overlook. Federated Learning augments the methodology by permitting the model to acquire knowledge from data from various dispersed sources while maintaining confidentiality, thereby enhancing detection precision and resilience against a wider array of attacks.The AI-driven model performs noticeably better than current algorithms in comparison, as seen by comparison findings, in terms of detection accuracy, response time, and flexibility to new and unknown threats. Along with lowering the total computing strain on cloud systems, the suggested method also lowers the frequency of false positives. The AI-driven paradigm is especially well-suited for large-scale, dynamic cloud settings with high and constantly changing security requirements because of these improvements. This work opens the door for more proactive, effective, and scalable cloud security systems that are capable of real-time, autonomous threat detection and mitigation.