國立虎尾科技大學 |

Cyber Security Meets Machine Learning

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Cyber Security Meets Machine Learning/ edited by Xiaofeng Chen, Willy Susilo, Elisa Bertino.
其他題名:	ss
其他作者:	Bertino, Elisa.
面頁冊數:	IX, 163 p. 41 illus., 24 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computer Applications. -
電子資源:	https://doi.org/10.1007/978-981-33-6726-5
ISBN:	9789813367265

Cyber Security Meets Machine Learning
Cyber Security Meets Machine Learning[electronic resource] /ssedited by Xiaofeng Chen, Willy Susilo, Elisa Bertino. - 1st ed. 2021. - IX, 163 p. 41 illus., 24 illus. in color.online resource.

Chapter 1. IoT Attacks and Malware -- Chapter 2. Machine Learning-based Online Source Identification for Image Forensics -- Chapter 3. Reinforcement Learning Based Communication Security for Unmanned Aerial Vehicles -- Chapter 4. Visual Analysis of Adversarial Examples in Machine Learning -- Chapter 5. Adversarial Attacks against Deep Learning-based Speech Recognition Systems -- Chapter 6. Secure Outsourced Machine Learning -- Chapter 7. A Survey on Secure Outsourced Deep Learning.

Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.

ISBN: 9789813367265

Standard No.: 10.1007/978-981-33-6726-5doiSubjects--Topical Terms:

669785
Computer Applications.

LC Class. No.: QA76.9.A25

Dewey Class. No.: 005.8

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