AI-Driven Privacy Security and Operational Intelligence in Cloud Computing Environments
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Abstract
Cloud computing has become the backbone of modern digital infrastructure, enabling scalable, flexible, and cost-efficient solutions for organizations worldwide. However, the rapid adoption of cloud services has introduced significant challenges related to data privacy, security threats, and operational complexities. Artificial Intelligence (AI) has emerged as a transformative technology capable of addressing these challenges by enhancing privacy protection, strengthening security mechanisms, and improving operational intelligence within cloud environments. This paper explores the integration of AI-driven techniques in cloud computing to ensure robust privacy and security while optimizing system performance. AI models, including machine learning and deep learning algorithms, enable real-time threat detection, anomaly identification, predictive analytics, and automated response systems. Furthermore, AI enhances data governance by supporting encryption management, access control, and compliance monitoring. The study also examines current research trends, methodologies, and frameworks that leverage AI for intelligent cloud operations. By combining AI with cloud technologies, organizations can achieve proactive security, adaptive risk management, and efficient resource utilization. This research highlights the importance of AI-driven approaches in building secure, resilient, and intelligent cloud ecosystems capable of addressing evolving cyber threats and operational demands.
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