Network Intrusion Detection using Deep Learning A Feature Learning Approach /

• Κύριοι συγγραφείς: Kim, Kwangjo (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Aminanto, Muhamad Erza (http://id.loc.gov/vocabulary/relators/aut), Tanuwidjaja, Harry Chandra (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: SpringerBriefs on Cyber Security Systems and Networks,
• Θέματα: Data protection.; Artificial intelligence.; Computer security.; Wireless communication systems.; Mobile communication systems.; Big data.; Data mining.; Security.; Artificial Intelligence.; Systems and Data Security.; Wireless and Mobile Communication.; Big Data.; Data Mining and Knowledge Discovery.

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...

Πίνακας περιεχομένων:

• Chapter 1 Introduction
• Chapter 2 Intrusion Detection Systems
• Chapter 3 Classical Machine Learning and Its Applications to IDS
• Chapter 4 Deep Learning
• Chapter 5 Deep Learning-based IDSs
• Chapter 6 Deep Feature Learning
• Chapter 7 Summary and Further Challenges.