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Shared Autoencoder-Based Unified Intrusion Detection Across Heterogeneous Datasets for Binary and Multi-Class Classification Using a Hybrid CNN–DNN Model
Today's article comes from the journal of Machine Learning and Knowledge Extraction. The authors are Kamal et al., from the German University in Cairo (GUC). In this paper they build can intrusion detection system (IDS) that can operate at multiple network-layers at once. How? It uses a shared autoencoder with projection layers that map each level of data into a common latent space.
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By JournalClub.ioToday's article comes from the journal of Machine Learning and Knowledge Extraction. The authors are Kamal et al., from the German University in Cairo (GUC). In this paper they build can intrusion detection system (IDS) that can operate at multiple network-layers at once. How? It uses a shared autoencoder with projection layers that map each level of data into a common latent space.