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portada Intrusion Detection System based on deep learning
Type
Physical Book
Author
Publisher
Language
English
Pages
108
Format
Paperback
Dimensions
22.9 x 15.2 x 0.7 cm
Weight
0.17 kg.
ISBN13
9786205985717
Categories

Intrusion Detection System based on deep learning

Junior Momo Ziazet (Author) · Our Knowledge Publishing · Paperback

Intrusion Detection System based on deep learning - Momo Ziazet, Junior

New Book Imported to Netherlands
Delivery: 07 Sep - 09 Sep Shipping: 14 to 15 business days.
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Synopsis "Intrusion Detection System based on deep learning"

This work focuses on the development of a new approach based on deep learning to implement an efficient and flexible intrusion detection system using the behavioral approach and mainly intended for critical infrastructures and industrial control systems. Based on the assumption that modeling the normal network behavior of industrial control systems is feasible and reliable, because the operations performed in these systems are quite stationary and repetitive, Convolutional Neural Networks (CNN), a deep learning technique, are used on the NSL-KDD dataset, a reference dataset used for the implementation of intrusion detection systems. The performance of the approach is presented and compared to some previous works. The metrics used include the percentage of correct classification, accuracy and false positives show that the proposed approach improves the performance of previous systems.

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