Abstract:
The rapid development of cloud computing has changed the way organizations store, retrieve, and secure data, providing incredible scalability at a cost and posing new and challenging cyber threats that most security tools are incapable of determining effectively. In this thesis, artificial intelligence is explored to enhance the threat detection and prevention preparedness in the cloud setting, using a well-designed hybrid dataset that combines the data on synthetic network traffic with more detailed information on the governance of different organizations. Several models of AI were also evaluated, such as Random Forests, XGBoost on the basis of detecting various types of attacks, as well as the models of Logistic Regression, Gradient-Boosted Trees, and Multilayer Perceptions on the basis of predicting the security posture maturity. The results indicate that AI can provide and identify cyber threats with very high precision and issue corresponding ratings of organizational readiness to prevent an attack. It is observed that the XGBoost had the best accuracy of detection and Logistic Regression models provided the interpretable and accurate prediction of governance score. This two-pipe approach to reactive detection and proactive prevention is a response to the comprehensive needs of the modern cloud security. However, there are a number of difficulties, in particular, to achieve the transparency of the models, protect the sensitive information, and be ready to adjust to the new changes in the nature of threats in the multifaceted clouds. Furthermore, the factors of such consideration of the operation, as the rapidity of the detection, as well as the continuity between the new security setups and the old ones, are also paramount. The thesis mentions such directions of future research as the development of adaptive AI systems that would enable it to learn in real-time, collaboratively privacy-safe methods, and more fundamental integration with zero-trust systems and the development of explainable AI tools as the tools of building trust and ensuring effective human oversight. Overall, this paper has very good information that the use of intelligent artificial intelligence to secure the cloud can be valuable in a balanced way to false threat detection methods and efficient governance check-ups as a good foundation of organizations that plan to deploy intelligent, responsible, and trustful defenses on the cloud.
