Integration of Automated Testing In Cybersecu...

Integration of Automated Testing In Cybersecurity Risk Mitigation

Author Name : Abhishek Nimdia

ABSTRACT The article examines vulnerabilities inherent in network infrastructures composed of interconnected hardware and software components and evaluates risk assessment methods using frameworks such as the Common Vulnerability Scoring System (CVSS). The study explores modern penetration testing approaches that integrate automated tools with expert analysis to effectively identify system weaknesses. Particular attention is given to attack graph modeling and the application of machine learning methods, specifically reinforcement learning, to optimize testing strategies. Experimental results demonstrate that RL-based agents can iteratively refine their actions to approximate near-optimal strategies, outperforming random approaches and indicating promising directions for future cybersecurity research. This article will be useful for cybersecurity professionals, network administrators, and researchers seeking to enhance risk mitigation strategies in complex network infrastructures through the integration of automated penetration testing and reinforcement learning.