{
"item_title" : "Optimized Deep Learning for Network Intrusion Detection",
"item_author" : [" Bhushan Deore "],
"item_description" : "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.",
"item_img_path" : "https://covers2.booksamillion.com/covers/bam/6/20/844/021/6208440211_b.jpg",
"price_data" : {
"retail_price" : "90.00", "online_price" : "90.00", "our_price" : "90.00", "club_price" : "90.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : ""
}
}
Optimized Deep Learning for Network Intrusion Detection
Overview
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.
This item is Non-Returnable
Customers Also Bought
Details
- ISBN-13: 9786208440213
- ISBN-10: 6208440211
- Publisher: LAP Lambert Academic Publishing
- Publish Date: April 2025
- Dimensions: 9 x 6 x 0.48 inches
- Shipping Weight: 0.63 pounds
- Page Count: 208
Related Categories
