Aug 2026· Cluster Computing· Vol 29· 0 citations· 36 references
TL;DR
Experimental results on standard intrusion detection benchmarks show that the proposed framework improves detection performance under limited-label conditions while reducing training time, memory usage, and inference latency relative to dense-attention baselines, indicating that the proposed framework offers a practical balance among detection accuracy, computational efficiency, and explainability, making it suitable for deployment in resource-constrained and real-time network security environments.
A new graph-guided contrastive transformer-based intrusion detection system (GCT-IDS) which aims at improving detection accuracy and robustness and preserving real-time feasibility is presented.
This study provides a high-precision, lightweight, and strongly generalizable multi-class intrusion detection model for resource-constrained vehicular environments.
Ya-Li Hao, He Bai, A. Siya et al.· Scientific Reports· 0 citations
The Sequential Submodular Feature-Sample Selection (SSFSS) framework is proposed, a theoretically grounded approach that sequentially optimizes the feature and sample spaces to reduce training cost while preserving detection fidelity, and is positioned as an efficient update-aware preprocessing framework whose measured...
Mohammed Nagah Amr, Ahmed S. Elliethy, T. Mekkawy et al.· Scientific Reports· 0 citations
X-SPUR is presented, an explainable, surprisal-based, protocol-aware unsupervised reasoning framework that instead represents raw packet fields as token sequences, learns benign traffic patterns through causal language modeling, and detects anomalies from per-token cross-entropy surprisal.
Networked manufacturing couples sensors, programmable logic controllers, and industrial gateways to production that cannot simply be paused. An intrusion detector in this setting must control false alarms and edge-resource use as well as detect attacks. Industrial Internet of Things (IIoT) edge nodes add three practica...
Jing Li, Shu-Hao Shen, Kang-Rui Xu et al.· ICST Transactions on Scalabl...· 0 citations
