AI-POWERED CYBERSECURITY THREAT DETECTION IN CLOUD ENVIRONMENTS

Abstract

The rapid evolution of cloud computing has revolutionized the digital landscape, offering scalable, on-demand resources for organizations worldwide. However, the extensive adoption of cloud environments has simultaneously introduced a plethora of cybersecurity threats ranging from data breaches and Advanced Persistent Threats (APTs) to sophisticated malware attacks. Traditional security defenses often reliant on static rule-based systems frequently prove inadequate for identifying and mitigating the complex, ever-evolving nature of modern cyber threats. Artificial Intelligence (AI) has emerged as a vital component of next-generation cybersecurity, enabling real-time threat detection, behavior-based anomaly recognition, and predictive analytics. In this paper, we explore cutting-edge AI-driven cybersecurity solutions specifically tailored for cloud infrastructures. We present a comprehensive framework for AI-based threat detection, analyze real-world use cases, discuss challenges in implementation, and propose future directions such as federated learning and blockchain integration. By demonstrating the effectiveness of AI in proactive threat hunting, automated incident response, and adaptive security measures, this research highlights AI’s transformative role in safeguarding cloud environments.