國立虎尾科技大學 |

Network Intrusion Detection using Deep Learning = A Feature Learning Approach /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Network Intrusion Detection using Deep Learning/ by Kwangjo Kim, Muhamad Erza Aminanto, Harry Chandra Tanuwidjaja.
其他題名:	A Feature Learning Approach /
作者:	Kim, Kwangjo.
其他作者:	Aminanto, Muhamad Erza.
面頁冊數:	XVII, 79 p. 30 illus., 11 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Data protection. -
電子資源:	https://doi.org/10.1007/978-981-13-1444-5
ISBN:	9789811314445

Network Intrusion Detection using Deep Learning = A Feature Learning Approach /
Kim, Kwangjo.

Network Intrusion Detection using Deep LearningA Feature Learning Approach /[electronic resource] :by Kwangjo Kim, Muhamad Erza Aminanto, Harry Chandra Tanuwidjaja. - 1st ed. 2018. - 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,.

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.

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.

ISBN: 9789811314445

Standard No.: 10.1007/978-981-13-1444-5doiSubjects--Topical Terms:

557764
Data protection.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

Network Intrusion Detection using Deep Learning = A Feature Learning Approach /
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