Network Intrusion Detection using Deep Learning A Feature Learning Approach /

• Main Authors: Kim, Kwangjo (Author, 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)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: SpringerBriefs on Cyber Security Systems and Networks,
• Subjects: 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...