The Next-Generation Cloud Security Model: AI-Powered Zero Trust and Adaptive Threat Prevention
Venkata M Kancherla · International Journal of Emerging Trends in Computer Science and Information Technology · 2025
Cloud computing has revolutionized the way enterprises manage their IT resources, but it has also introduced new challenges in terms of security. Traditional cloud security models, which primarily rely on perimeter-based defences, have proven inadequate in addressing sophisticated cyber threats and insider attacks. The shift towards next-generation security frameworks has led to the adoption of Zero Trust Architecture (ZTA) and Adaptive Threat Prevention (ATP) models, both of which emphasize continuous monitoring and dynamic responses to emerging threats. The integration of Artificial Intelligence (AI) into these models promises to further enhance cloud security by providing predictive analytics, automating threat responses, and facilitating real-time decision-making. Zero Trust, based on the principle of "never trust, always verify," ensures that no user or device is implicitly trusted, regardless of its location within the network. When coupled with AI, Zero Trust becomes more efficient, enabling adaptive and context-aware security policies that are continuously updated based on real-time data. ATP, on the other hand, utilizes machine learning and AI to predict, detect, and mitigate threats before they can cause damage, ensuring that security measures evolve in line with the constantly changing threat landscape. This paper explores the synergy between AI-powered Zero Trust and Adaptive Threat Prevention, examining how these technologies can transform cloud security. The combination of these advanced models offers significant advantages, including enhanced detection of anomalous behaviour, automated incident response, and scalability. However, challenges remain in implementing these systems, particularly in terms of complexity, resource requirements, and data privacy concerns. This work aims to provide a comprehensive understanding of these emerging models, their potential benefits, and the challenges associated with their adoption in cloud environments