Artificial Intelligence-Powered Cybersecurity Solutions: Strengthening the Defense of Cloud Infrastructure with Machine Learning and Predictive Threat Analytics

Artificial Intelligence-Powered Cybersecurity Solutions: Strengthening the Defense of Cloud Infrastructure with Machine Learning and Predictive Threat Analytics

연구 분야: Safety

학회: 2025 Global Conference in Emerging Technology (GINOTECH)

The attack surface for cyber threats has grown substantially due to the fast use of cloud infrastructure across numerous industries, highlighting the need for strong and adaptable security solutions. In this article, we take a look at the possibilities of cybersecurity solutions driven by AI, specifically at how ML and predictive threat analytics might strengthen cloud environment defences. Compared to older rule-based systems, cybersecurity systems that use AI are better able to sift through mountains of data, spot outliers, and anticipate new risks. By combining ML models, we can learn from past and present data in real-time, which automates the detection and response to new attack vectors. Organisations may proactively put defence measures in place before breaches happen thanks to predictive threat analytics, which is driven by AI and provides insights into potential future attacks. This study highlights the importance of AI in cloud infrastructure incident response by enhancing the accuracy of threat detection, decreasing the number of false positives, and optimising the allocation of resources. At the end of the article, we talk about where AI-driven cloud cybersecurity is going from here and what the obstacles are, such as data privacy worries and the necessity for open AI models.