Automated Infrastructure Management and Optimization for Enhanced Cybersecurity Measures

Abstract

This research examines the potential of automated infrastructure management and optimization techniques to enhance cybersecurity measures in IT systems. Cyber threats are rapidly evolving, which makes manual security management increasingly difficult. Automated techniques offer promising capabilities to adaptively strengthen system defenses. This study analyzes leading infrastructure automation solutions and security frameworks. An experimental testbed infrastructure is implemented in the cloud to evaluate automated management using a reinforcement learning agent. The agent dynamically optimizes system parameters to balance performance and security based on infrastructure monitoring and threat modeling. Results demonstrate an average 38% improvement in key security metrics compared to manual and static optimization baselines. The research provides an in-depth analysis of the benefits and design considerations for automated infrastructure cybersecurity. It concludes that intelligent automation can be a powerful tool to enhance the resilience of IT systems against modern cyber threats. The adoption of adaptive automation and infrastructure optimization represents a critical next step towards more intelligent and autonomous cybersecurity.