國立高雄大學圖資館 |

Language: English

Back

Cyber security meets machine learning

Bertino, Elisa.

Cyber security meets machine learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cyber security meets machine learningedited by Xiaofeng Chen, Willy Susilo, Elisa Bertino.
other author:	Chen, Xiaofeng.
Published:	Singapore :Springer Singapore :2021.
Description:	ix, 163 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Machine learningSecurity measures.
Online resource:	https://doi.org/10.1007/978-981-33-6726-5
ISBN:	9789813367265$q(electronic bk.)

Cyber security meets machine learning
Cyber security meets machine learning[electronic resource] /edited by Xiaofeng Chen, Willy Susilo, Elisa Bertino. - Singapore :Springer Singapore :2021. - ix, 163 p. :ill., digital ;24 cm.

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$q(electronic bk.)

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

897594
Machine learning
--Security measures.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Cyber security meets machine learning
LDR:02804nmm a2200337 a 4500 001 601997
003 DE-He213
005 20210707072234.0
006 m d
007 cr nn 008maaau
008 211112s2021 si s 0 eng d
020 $a 9789813367265$q(electronic bk.)
020 $a 9789813367258$q(paper)
024 7 $a 10.1007/978-981-33-6726-5 $2 doi
035 $a 978-981-33-6726-5
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UR $2 bicssc
072 7 $a COM053000 $2 bisacsh
072 7 $a UR $2 thema
072 7 $a UTN $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .C994 2021
245 0 0 $a Cyber security meets machine learning $h [electronic resource] / $c edited by Xiaofeng Chen, Willy Susilo, Elisa Bertino.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a ix, 163 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Machine learning $x Security measures. $3 897594
650 0 $a Computer security. $3 184416
650 1 4 $a Systems and Data Security. $3 274481
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a Information Systems and Communication Service. $3 274025
650 2 4 $a Computer Communication Networks. $3 218087
650 2 4 $a Computer Applications. $3 273760
700 1 $a Chen, Xiaofeng. $3 530742
700 1 $a Susilo, Willy. $3 277028
700 1 $a Bertino, Elisa. $3 284965
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-981-33-6726-5
950 $a Computer Science (SpringerNature-11645)