Citation :

Vaishali Nagpure , 2023. "AI-Powered Network Infrastructure Audits: Enhancing Efficiency and Security in Data Centers", ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 1, Issue 3: 124-130.

Abstract :

In the evolving landscape of modern IT infrastructure, organizations are increasingly adopting hybrid environments that combine on-premises data centers with cloud solutions to meet scalability, flexibility, and operational efficiency needs. However, managing the security and performance of such complex environments introduces unique challenges, particularly in areas like network segmentation, vulnerability management, and real-time threat detection. This case study explores the implementation of an AI-powered network infrastructure audit and security framework for a global retail company operating in both on-premises and cloud environments. The company’s data center infrastructure relies on Cisco devices, including Cisco ACI (Application Centric Infrastructure) for network segmentation, Cisco Firepower NGFW for intrusion prevention, and Cisco Umbrella for DNS-level protection. The core of this approach involves leveraging AI-driven tools to automate vulnerability management, threat detection, and response across both on-premises systems and cloud environments (AWS, Azure). The study illustrates how Cisco ACI and AWS Security Hub were used to segment networks and isolate sensitive data, minimizing the attack surface. Furthermore, the integration of Qualys VMDR for automated vulnerability scanning and patch management, combined with Ansible for efficient patch deployment, improved operational efficiency and reduced manual intervention in vulnerability remediation. Cisco Tetration provided enhanced visibility into workload behaviors across both environments, ensuring that unauthorized lateral movements were prevented. The implementation of AI-driven security analytics through Cisco Firepower and Umbrella allowed for rapid identification and mitigation of potential threats. Additionally, the study highlights the importance of automated compliance reporting, with tools like ServiceNow integrated for tracking remediation efforts and generating compliance reports for industry standards such as PCI-DSS and GDPR. By deploying a combination of advanced network segmentation, real-time threat detection, and automated remediation, the company achieved significant improvements in its security posture, operational efficiency, and compliance. This case study serves as a comprehensive example of how AI-powered security tools and Cisco devices can be effectively integrated to address the complexities of managing a hybrid IT infrastructure while ensuring that both on-premises and cloud environments remain secure, efficient, and compliant. The results of this implementation demonstrate the value of combining cutting-edge security technologies with automation to drive proactive risk management and operational excellence

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Keywords :

AI-Powered Network Audits, Micro-Segmentation, Vulnerability Management, Cisco Security Tools, Compliance Automation.