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Deep Learning Algorithms Used in Intrusion Detection Systems -- A Review
Feb. 28, 2024, 5:11 a.m. | Richard Kimanzi, Peter Kimanga, Dedan Cherori, Patrick K. Gikunda
cs.CR updates on arXiv.org arxiv.org
Abstract: The increase in network attacks has necessitated the development of robust and efficient intrusion detection systems (IDS) capable of identifying malicious activities in real-time. In the last five years, deep learning algorithms have emerged as powerful tools in this domain, offering enhanced detection capabilities compared to traditional methods. This review paper studies recent advancements in the application of deep learning techniques, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Belief Networks (DBN), Deep …
algorithms arxiv attacks capabilities cs.cr deep learning detection development domain ids intrusion intrusion detection malicious network network attacks real review systems tools
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