Abstract & Overview
Cloud scalability needs to adapt to the constantly shifting needs of the marketplace. But as computing has become a crucial part of modern IT systems, giving businesses flexibility and technology advances, a new era of cybersecurity threats has emerged, with hackers using ever-more-advanced tactics to compromise cloud networks. Wide-ranging effects of such breaches may include lost data, monetary losses, harm to one's reputation, and legal responsibilities. Creating a strong security framework is essential to successfully protecting cloud infrastructure in light of these issues. Advanced capabilities for analyzing vast volumes of data produced in real-time within cloud infrastructures are offered by artificial intelligence (AI) technology. This makes identifying unusual behavior and possible security breaches possible early on. AI systems can more accurately and effectively detect patterns, spot malicious activities, and foresee emerging dangers by utilizing machine learning (ML) algorithms, deep learning models, and natural language processing techniques. By continuously learning from historical data and adjusting to changing attack vectors, AI-driven threat detection systems assist cloud security teams in staying ahead of adversaries and enhancing the resilience and integrity of cloud-based services. In conclusion, the suggested framework is a thorough approach to cloud security, combining cutting-edge technology with ongoing improvement to safeguard cloud infrastructure, reduce risks, and successfully negotiate the always-changing cybersecurity threat landscape.