Kim, Kwangjo. <br/><br/>
Network Intrusion Detection using Deep Learning  A Feature Learning Approach /  [electronic resource] : 
by Kwangjo Kim, Muhamad Erza Aminanto, Harry Chandra Tanuwidjaja. 
 - XVII, 79 p. 30 illus., 11 illus. in color.  online resource. 
 - SpringerBriefs on Cyber Security Systems and Networks,  2522-5561. .
 - SpringerBriefs on Cyber Security Systems and Networks, .
<br/><br/>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. 
<br/><br/> Online version restricted to NUS staff and students only through NUSNET. 
<br/><br/> 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. 
<br/><br/><br/>Mode of access: World Wide Web. <br/>System requirements: Internet connectivity; World Wide Web browser. 
<br/><br/><label>ISBN: </label>9789811314445 
<br/><br/><label>Standard No.: </label>10.1007/978-981-13-1444-5  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Data protection.<br/>Artificial intelligence.<br/>Wireless communication systems.<br/>Mobile communication systems.<br/>Big data.<br/>Data mining.<br/>Security.