AUTOMON TRANSFORMING MODELS INTO CLOUD SECURITY MONITORS

Abstract

With the growing reliance on cloud computing, ensuring the security and reliability of cloud infrastructures has become a critical concern. This study introduces AutoMon, a model-driven framework that automatically generates cloud monitors from system and security models to detect, prevent, and respond to potential threats. By translating high-level cloud architecture and security specifications into executable monitoring components, AutoMon provides real-time oversight of cloud resources, access controls, and network activities. The approach enhances proactive threat detection, reduces human intervention, and ensures compliance with security policies. Experimental evaluations demonstrate that AutoMon effectively identifies anomalies, mitigates security risks, and improves the overall resilience of cloud environments with minimal performance overhead. This research highlights the potential of automated, model-based monitoring systems to advance cloud security management and support robust, trustworthy cloud services.