Network Intrusion Detection using Deep Learning

Released on by Kwangjo Kim
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  • Network Intrusion Detection using Deep Learning Book Detail

  • Author : Kwangjo Kim
  • Release Date : 2018-10-02
  • Publisher : Springer
  • Genre : Computers
  • Pages : 79
  • ISBN 13 : 9789811314438
  • File Size : 51,51 MB
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Network Intrusion Detection using Deep Learning by Kwangjo Kim PDF Summary

Book Description: This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.

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