Secure SustainNet: A Multi-Objective Framework for Enhancing Security and Sustainability in Data Centers - Vijayakumar, Ramachandran; Duraimutharasan, N. (Journal of Neonatal Surgery, 2025)
This paper introduces the SecureSustainNet Framework, a novel approach designed to enhance security and sustainability within data centers. The framework employs a multi-objective optimization technique that harmonizes security measures with energy efficiency. It includes six core algorithms: Intrusion Detection System with Anomaly Detection, AES-256 Encryption with Optimized Key Management, Role-Based Access Control with Dynamic Policy Adjustment, Dynamic Resource Allocation, Energy Consumption Monitoring and Optimization, and Renewable Energy Integration. The framework was implemented and evaluated using the ns-3 network simulator. The evaluation results demonstrate significant advancements in both security and sustainability. The Intrusion Detection System achieved an Anomaly Detection Rate (ADR) of 98.7%, reflecting high accuracy in threat identification. Encryption overhead was minimized to a 2.5% increase in processing time, showcasing efficient performance. The Role-Based Access Control system attained an effectiveness of 97.4% in preventing unauthorized access. Resource Utilization Efficiency (RUE) reached 85.2%, indicating effective resource management. The framework also achieved a 15.6% reduction in energy consumption and a Power Usage Effectiveness (PUE) of 1.25, signifying improved energy efficiency. These results underline the SecureSustainNet Framework’s effectiveness in integrating robust security measures with advanced sustainability practices, presenting it as a valuable model for optimizing data center operations.