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Random forest with differential privacy in federated learning framework for network attack detection and classification., , , и . Appl. Intell., 54 (17-18): 8132-8153 (сентября 2024)Comparative Evaluation of Machine Learning Algorithms for Network Intrusion Detection and Attack Classification., , и . IJCNN, стр. 1-8. IEEE, (2022)Multi-Objective Optimization on Autoencoder for Feature Encoding and Attack Detection on Network Data., , и . GECCO Companion, стр. 379-382. ACM, (2023)Time-series Anomaly Detection and Classification with Long Short-Term Memory Network on Industrial Manufacturing Systems., , , , и . FedCSIS, том 35 из Annals of Computer Science and Information Systems, стр. 171-181. (2023)Federated Learning for Network Anomaly Detection in a Distributed Industrial Environment., , , , и . ICMLA, стр. 218-225. IEEE, (2023)Enhanced Simulation Environment to Support Research in Modular Manufacturing Systems., , и . IECON, стр. 1-6. IEEE, (2023)MIDAS: A Modular Ice Cream Factory Dataset on Anomalies in Sensors., , , и . (декабря 2022)Simulation Environment for Modular Automation Systems., , , , , и . IECON, стр. 1-6. IEEE, (2022)Feature encoding with autoencoder and differential evolution for network intrusion detection using machine learning., , и . GECCO Companion, стр. 2152-2159. ACM, (2022)A Modular Ice Cream Factory Dataset on Anomalies in Sensors to Support Machine Learning Research in Manufacturing Systems., , , и . IEEE Access, (2023)