aceGreen-aware intrusion detection systems: A sustainability-driven approach to network security
The rapid proliferation of Internet of Things (IoT) devices has intensified network security challenges. Simultaneously, growing computational demands raise critical concerns about energy consumption and environmental sustainability. This paper proposes a Green-Aware Intrusion Detection System (GA-IDS) integrating sustainability metrics with machine learning to balance detection performance and energy efficiency. The framework employs a lightweight convolutional neural network optimized for resource-constrained…
A lightweight, carbon-aware neural network intrusion detector used 43% less energy than traditional deep learning detectors while keeping 98.7% accuracy on benchmark datasets.
The evidence is limited to experimental evaluation on three benchmark datasets, so results do not by themselves show performance in live deployments.
Evidence
- Peer-reviewedPLOS One2026-10-15
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Truvace Impact Record TRV-2026-1969, v1: “Green-aware intrusion detection systems: A sustainability-driven approach to network security.” Truvace, 2026-10-20. /record/TRV-2026-1969 (accessed at citation time). sha256 6cddf87f08fc2553…
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