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A Cascade-structured Meta-Specialists Approach for Neural Network-based Intrusion Detection.

, , , и . CCNC, стр. 1-6. IEEE, (2019)

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Aurélie Labonne

Maxime Lorrillere

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A Cascade-structured Meta-Specialists Approach for Neural Network-based Intrusion Detection., , , и . CCNC, стр. 1-6. IEEE, (2019)Estimating class separability of text embeddings with persistent homology., , , , , и . Trans. Mach. Learn. Res., (2024)Predicting Bandwidth Utilization on Network Links Using Machine Learning., , и . EuCNC, стр. 242-247. IEEE, (2020)Short-Term Flow-Based Bandwidth Forecasting using Machine Learning., , , и . CoRR, (2020)Unsupervised Protocol-based Intrusion Detection for Real-world Networks., , , и . ICNC, стр. 299-303. IEEE, (2020)Anomaly Detection in Vehicle-to-Infrastructure Communications., , , и . VTC Spring, стр. 1-6. IEEE, (2018)Priority Flow Admission and Routing in SDN: Exact and Heuristic Approaches., , , и . NCA, стр. 1-10. IEEE, (2020)Anomaly-based network intrusion detection using machine learning. (Détection d'intrusion réseau par anomalies avec apprentissage automatique).. Polytechnic Institute of Paris, France, (2020)An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning., , , , , и . CoRR, (2023)Dynamic Link Network Emulation and Validation of Execution Datasets., , , , , и . ENASE (Selected Papers), том 1829 из Communications in Computer and Information Science, стр. 116-138. Springer, (2022)