Cloud Security Automation Using AI-Driven Threat Response Systems

Abstract

The increasing complexity of cloud environments has made manual threat detection and response insufficient for modern security challenges. This paper proposes an AI-driven threat response system that automates incident detection, analysis, and mitigation in real-time. The system leverages deep learning models to analyze network traffic and system logs, identifying anomalous patterns indicative of cyberattacks. It integrates with cloud-native security tools to orchestrate automated responses, such as isolating affected instances and modifying firewall rules. Performance analysis demonstrates that the AI-driven system reduces incident response time and minimizes the impact of breaches. The study concludes that automation using AI enhances the scalability and effectiveness of cloud security operations.