Generating detectors from anomaly samples via negative selection for network intrusion detection. [PDF]
Li Z, Wei X, Li C, Sun J.
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Multimodal fusion based few-shot network intrusion detection system. [PDF]
Xu C, Zhan Y, Wang Z, Yang J.
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In-vehicle network intrusion detection systems: a systematic survey of deep learning-based approaches. [PDF]
Luo F +5 more
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GeNIS: A modular dataset for network intrusion detection and classification. [PDF]
Silva M +5 more
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A novel adaptive network intrusion detection system for internet of things. [PDF]
Aravamudhan P, T K.
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Research on Network Intrusion Detection Based on Weighted Histogram Algorithm for In-Vehicle Ethernet. [PDF]
Wang Y, Wu Y, Xu Y, Zhang K, Xu Y.
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Vehicular Network Intrusion Detection Using a Cascaded Deep Learning Approach with Multi-Variant Metaheuristic. [PDF]
Manderna A +5 more
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training. [PDF]
Huang W +5 more
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Research on Adaptive 1DCNN Network Intrusion Detection Technology Based on BSGM Mixed Sampling. [PDF]
Ma W, Gou C, Hou Y.
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CSCVAE-NID: A Conditionally Symmetric Two-Stage CVAE Framework with Cost-Sensitive Learning for Imbalanced Network Intrusion Detection. [PDF]
Wang Z, Yu X.
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