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References from Deployment-oriented evaluation of deep learning network intrusion detection systems. Local targets link to admitted publications; unresolved targets remain external evidence.
Trustworthy adaptive AI for real-time intrusion detection in industrial IoT security
10.3390/iot6030053 · 2025 · External reference
Dataset-centric evaluation of federated intrusion detection models in IoT networks
10.1038/s41598-025-32567-w · 2026 · External reference
Machine learning in network intrusion detection: a cross-dataset generalization study
10.1109/access.2024.3472907 · 2024 · External reference
Class incremental learning for network-agnostic intrusion detection systems
2025 · External reference
Deep learning-driven methods for network-based intrusion detection systems: a systematic review
10.1016/j.icte.2025.01.005 · 2025 · External reference
Few-shot class-incremental learning for network intrusion detection systems
10.1109/ojcoms.2024.3481895 · 2024 · External reference
Toward open-world network intrusion detection via open recognition and inspection
10.1109/tifs.2025.3608666 · 2025 · External reference
Cross-dataset temporal and semantic generalization of intrusion detection models for the future internet
10.3390/fi18040194 · 2026 · External reference
Unknown intrusion traffic detection method based on unsupervised learning and open-set recognition
10.1038/s41598-025-01084-1 · 2025 · External reference
Scalable and generalizable cross-domain invariant network analysis and intrusion detection system using deep learning
10.1109/ojcoms.2026.3677692 · 2026 · External reference
A transfer-aware, deployment-oriented evaluation framework for netflow-based intrusion detection systems (TAN-IDS)
10.1371/journal.pone.0346801 · 2026 · External reference
The choice of training data and the generalizability of machine learning models for network intrusion detection systems
10.3390/app15158466 · 2025 · External reference
Multi-source refined adversarial domain adaptation with transfer complementarity infusion for IoT intrusion detection under limited samples
10.1016/j.eswa.2024.124352 · 2024 · External reference
Adaptive semi-supervised algorithm for intrusion detection and unknown attack identification
10.3390/app15041709 · 2025 · External reference
FORT-IDS: a federated, optimized, robust and trustworthy intrusion detection system for IIoT security
10.1038/s41598-025-31025-x · 2026 · External reference
Intrusion detection in software-defined networking using hybrid Bayesian model averaging for reliable uncertainty quantification
10.1016/j.comnet.2025.111436 · 2025 · External reference
Deep learning-based network intrusion detection systems: a systematic literature review
10.1007/978-3-031-78255-8_13 · 2025 · External reference
FedMSE: semi-supervised federated learning approach for IoT network intrusion detection
10.1016/j.cose.2025.104337 · 2025 · External reference
nNFST: a single-model approach for multiclass novelty detection in network intrusion detection systems
10.1016/j.jnca.2025.104128 · 2025 · External reference
IDAC: federated learning-based intrusion detection using autonomously extracted anomalies in IoT
10.3390/s24103218 · 2024 · External reference
Calibrated uncertainty estimation for trustworthy deep IoT attack detection
10.1109/tdsc.2025.3598350 · 2025 · External reference
A review on intrusion detection datasets: tools, processes, and features
10.1016/j.comnet.2025.111177 · 2025 · External reference
A systematic literature study of machine learning techniques based intrusion detection: datasets, models, challenges, and future directions
10.1186/s40537-025-01323-2 · 2025 · External reference
A novel open set energy-based flow classifier for network intrusion detection
10.1016/j.cose.2025.104569 · 2025 · External reference
Federated transfer learning for rare attack class detection in network intrusion detection systems
10.1038/s41598-025-02068-x · 2025 · External reference
Enhancing trustworthiness in ML-based network intrusion detection with uncertainty quantification
10.1007/s40860-024-00238-8 · 2024 · External reference
Trustable network intrusion detection system through Wisdomnet and uncertainty measures
10.1109/lcn60385.2024.10639737 · 2024 · External reference
TriHID: towards verifiable domain adaptation-based IoT intrusion detection in heterogeneous environment
10.1016/j.eswa.2025.129543 · 2026 · External reference
Open set dandelion network for IoT intrusion detection
10.1145/3639822 · 2024 · External reference
Cross-dataset transformer-IDS with calibration and AUC optimization (evaluated on NSL-KDD, UNSW-NB15, CIC-IDS2017)
10.32604/jcs.2025.071627 · 2025 · External reference
Few-shot network intrusion detection method based on multi-domain fusion and cross-attention
10.1371/journal.pone.0327161 · 2025 · External reference
Towards trustworthy cybersecurity operations using Bayesian deep learning to improve uncertainty quantification of anomaly detection
10.1016/j.cose.2024.103909 · 2024 · External reference
A cross-domain intrusion detection method based on nonlinear augmented explicit features
10.1109/tnsm.2024.3444909 · 2025 · External reference
Wasserstein distance guided feature tokenizer transformer domain adaptation for network intrusion detection
10.1016/j.cose.2025.104562 · 2025 · External reference
TICPS: a trustworthy collaborative intrusion detection framework for industrial cyber-physical systems
10.1016/j.adhoc.2024.103517 · 2024 · External reference
