The Role of AI and Machine Learning in Enhancing Cyber Security in Cloud Platforms

Abstract

The growing reliance on cloud platforms has introduced a heightened need for robust cybersecurity measures. Traditional security methods, while effective, struggle to keep pace with evolving cyber threats. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in enhancing cloud security, offering dynamic and automated approaches to threat detection, prevention, and response. This paper explores the critical role of AI and ML in addressing key cybersecurity challenges within cloud environments. It reviews various AI/ML techniques such as supervised learning, deep learning, and reinforcement learning, demonstrating their effectiveness in identifying vulnerabilities and responding to sophisticated cyberattacks. Through a discussion of real-world case studies, the paper highlights the advantages of integrating AI/ML models in cloud security architectures. Additionally, the paper identifies existing limitations, such as adversarial attacks on AI systems and ethical concerns related to data privacy. Finally, it outlines future directions for leveraging AI/ML in creating proactive, adaptive, and secure cloud environments.