Enhancing Cloud Security and Efficiency Through AI-Driven Intrusion Detection and Machine Learning-Based Resource Management
Ravikumar Ch, Satyanarayana Nimmala, Isha Batra, Arun Malik, Praveen Kumar Malik · Advances in information security, privacy, and ethics book series · 2025
Cloud computing is essential to modern IT infrastructure but faces challenges in security and resource optimization. This chapter explores enhancing cloud environments using artificial intelligence (AI) and machine learning (ML). AI-driven intrusion detection systems (IDS) employ anomaly detection and predictive analytics to mitigate threats in real time, fortifying systems against sophisticated attacks. Simultaneously, ML-based resource management optimizes performance by analyzing usage patterns and predicting demands, ensuring cost-efficiency. The chapter highlights methodologies like deep learning and reinforcement learning, illustrating their application in improving cloud security and scalability. Emerging trends such as federated learning and quantum computing are also discussed, emphasizing the critical role of AI and ML in advancing sustainable and resilient cloud ecosystems.