Optimized Deep Learning for Network Intrusion Detection

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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.

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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.

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Pages: 208, Paperback, LAP Lambert Academic Publishing


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Merk LAP LAMBERT Academic Publishing
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  • 9786208440213
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