Research on optimization of distributed network security framework based on blockchain under green computing framework

Abstract

In the current fast-changing digital world, distributed networks are under severe threat in terms of security and efficiency. Their decentralized nature and expanding amount of data raise system complexity and vulnerability. At the same time, sustainable computing demands energy-efficient solutions for network operations. This research proposes a Distributed Network Security Framework Based on Blockchain within a Green Computing Framework. It introduces a Dynamic Whale Optimized Adjustable Graph Neural Network (DWO-AGNN) to assess network security. The model leverages blockchain’s decentralized and tamper-proof features, using smart contracts to enhance resilience against cyberattacks. The framework also focuses on reducing the energy footprint of security operations. Key performance metrics include security effectiveness, energy consumption, and throughput. Results show strong performance: availability at 99.0 %, integrity at 96.8 %, and confidentiality at 95.2 %. The system achieves 95.7 Megabits per Second (Mbps) throughput, reduces energy usage from 1.20 to 0.85, and cuts energy costs from $500 to $375. This research demonstrates that blockchain-based models can deliver high security while supporting environmentally responsible computing. The DWO-AGNN offers a practical solution for resilient, energy-efficient distributed networks.