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.
Intrusion detection systems (IDS) are very instrumental in protecting contemporary network infrastructures against the ever-advancing cyberattacks. Conventional signature-based and machine learning-enabled IDS solutions frequently have difficulty when it comes to high false-positive rates, inability to flexibly adapt t...
With the proliferation of intelligent connected vehicles, the Controller Area Network (CAN) bus, as the backbone of in-vehicle communication, is vulnerable to cyberattacks due to lack of authentication and encryption. Existing Intrusion Detection Systems (IDS) exhibit limitations in addressing data imbalance, complex a...
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
Automotive Ethernet carries heterogeneous multi-protocol traffic in modern in-vehicle networks, where labeled attack data are rarely available and the strongest prior unsupervised detector still relies on handcrafted traffic features. This article presents X-SPUR, an explainable, surprisal-based, protocol-aware unsuper...
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
