Optimized Deep Learning for Network Intrusion Detection
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This book targets young researchers exploring advanced network security techniques to counter evolving cyber threats. It presents innovative methods, including RNN-based cyber-attack detection and IDS with feature reduction. Additionally, it introduces optimization-driven deep learning models like DASO-Deep RNN, ADASO-Deep RNN, and Opt RCNN-LSTM for precise intrusion detection, ensuring high accuracy, sensitivity, and specificity.
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Beschrijving
Bol
This book targets young researchers exploring advanced network security techniques to counter evolving cyber threats. It presents innovative methods, including RNN-based cyber-attack detection and IDS with feature reduction. Additionally, it introduces optimization-driven deep learning models like DASO-Deep RNN, ADASO-Deep RNN, and Opt RCNN-LSTM for precise intrusion detection, ensuring high accuracy, sensitivity, and specificity.
Bol
This book targets young researchers exploring advanced network security techniques to counter evolving cyber threats. It presents innovative methods, including RNN-based cyber-attack detection and IDS with feature reduction. Additionally, it introduces optimization-driven deep learning models like DASO-Deep RNN, ADASO-Deep RNN, and Opt RCNN-LSTM for precise intrusion detection, ensuring high accuracy, sensitivity, and specificity.
AmazonPages: 208, Paperback, LAP Lambert Academic Publishing
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