SECURING THE CLOUD WITH GENERATIVE AI A FRAMEWORK FOR SAFE INTEGRATION INTO AWS-NATIVE SECURITY SERVICES

Generative Artificial Intelligence (GenAI) is rapidly transforming cloud security by enabling automated code generation, anomaly detection, and adaptive threat modeling.In Amazon Web Services (AWS), the integration of GenAI into native services such as GuardDuty, Identity and Access Management (IAM), and SageMaker offers significant opportunities to enhance threat detection and incident response.However, this integration also introduces new risks, including model exploitation, prompt injection, and data leakage, which can inadvertently expand the attack surface of cloud environments.This study proposes a framework for the secure adoption of GenAI within AWS-native security services. The framework addresses three critical dimensions: (i) identifying potential vulnerabilities arising from GenAI integration, (ii) developing defensive strategies and governance mechanisms to mitigate adversarial misuse, and(iii) evaluating GenAI-driven security enhancements through empirical benchmarks and case studies in AWS contexts.By balancing the dual role of GenAI-as both a defensive tool and a potential attack vector-this work aims to provide actionable guidance for organizations adopting GenAI to secure their AWS environments.The findings contribute to both research and practice by advancing the discourse on safe Sireesha Devalla https://iaeme.com/