Secure Web: Integrating AI Driven Vulnerability Management and Anomaly Detection in AWS Based E - Commerce Platforms

Sai Tarun Kaniganti

Abstract: Web applications have become integral to modern business operations, driving commerce, social interactions, and various services. However, their increasing usage has made them prime targets for hackers, necessitating robust security measures. This paper explores the most effective strategies for securing web applications, including developing secure architectures and integrating AI and ML to enhance security levels. Key technologies like Blockchain and Zero Trust Architecture (ZTA) are examined for their potential to further fortify web application security. The paper includes a use case featuring AWS and Data Science experiences in AI and ML-based real-world projects, demonstrating how advanced technologies and practices can provide comprehensive protection for users' sensitive data.

Keywords: web application security, AI, machine learning, Blockchain, Zero Trust Architecture