國立虎尾科技大學 |

Artificial intelligence and cyber security in industry 4.0

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Artificial intelligence and cyber security in industry 4.0/ edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi.
other author:	Sarveshwaran, Velliangiri.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	viii, 373 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Industrial applications. -
Online resource:	https://doi.org/10.1007/978-981-99-2115-7
ISBN:	9789819921157

Artificial intelligence and cyber security in industry 4.0
Artificial intelligence and cyber security in industry 4.0[electronic resource] /edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi. - Singapore :Springer Nature Singapore :2023. - viii, 373 p. :ill. (chiefly color), digital ;24 cm. - Advanced technologies and societal change,2191-6861. - Advanced technologies and societal change..

Introduction to Artificial Intelligence and Cyber Security for Industry -- Role of AI and its impact on the development of cyber security applications -- AI and IoT in Manufacturing and related Security Perspectives for Industry 4.0 -- IoT Security Vulnerabilities and Defensive Measures in Industry 4.0 -- Adopting Artificial Intelligence in ITIL for Information Security Management - Way forward in Industry 4.0 -- Intelligent Autonomous Drones in Industry 4.0 -- A review on automatic generation of attack trees and its application to automotive cybersecurity -- Malware Analysis using Machine Learning Tools and Techniques in IT Industry -- USE OF MACHINE LEARNING IN FORENSICS AND COMPUTER SECURITY -- Control of feed drives in CNC machine tools using artificial immune adaptive strategy -- Efficient Anomaly Detection for Empowering Cyber Security by Using Adaptive Deep Learning Model -- Intrusion Detection in IoT based Healthcare Using ML and DL approaches: A Case Study -- War Strategy Algorithm based GAN model for Detecting the Malware Attacks in Modern Digital Age -- ML algorithms for providing financial security in banking sectors with the prediction of loan risks -- Machine Learning based DDoS Attack Detection using Support Vector Machine -- Artificial Intelligence based Cyber Security Applications.

This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications.

ISBN: 9789819921157

Standard No.: 10.1007/978-981-99-2115-7doiSubjects--Topical Terms:

796380
Artificial intelligence
--Industrial applications.

LC Class. No.: TA347.A78

Dewey Class. No.: 006.3

Artificial intelligence and cyber security in industry 4.0
LDR:03328nam a2200337 a 4500 001 1105679
003 DE-He213
005 20230613191724.0
006 m d
007 cr nn 008maaau
008 231013s2023 si s 0 eng d
020 $a 9789819921157 $q (electronic bk.)
020 $a 9789819921140 $q (paper)
024 7 $a 10.1007/978-981-99-2115-7 $2 doi
035 $a 978-981-99-2115-7
040 $a GP $c GP
041 0 $a eng
050 4 $a TA347.A78
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
090 $a TA347.A78 $b A791 2023
245 0 0 $a Artificial intelligence and cyber security in industry 4.0 $h [electronic resource] / $c edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi.
260 $a Singapore : $c 2023. $b Springer Nature Singapore : $b Imprint: Springer,
300 $a viii, 373 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Advanced technologies and societal change, $x 2191-6861
505 0 $a Introduction to Artificial Intelligence and Cyber Security for Industry -- Role of AI and its impact on the development of cyber security applications -- AI and IoT in Manufacturing and related Security Perspectives for Industry 4.0 -- IoT Security Vulnerabilities and Defensive Measures in Industry 4.0 -- Adopting Artificial Intelligence in ITIL for Information Security Management - Way forward in Industry 4.0 -- Intelligent Autonomous Drones in Industry 4.0 -- A review on automatic generation of attack trees and its application to automotive cybersecurity -- Malware Analysis using Machine Learning Tools and Techniques in IT Industry -- USE OF MACHINE LEARNING IN FORENSICS AND COMPUTER SECURITY -- Control of feed drives in CNC machine tools using artificial immune adaptive strategy -- Efficient Anomaly Detection for Empowering Cyber Security by Using Adaptive Deep Learning Model -- Intrusion Detection in IoT based Healthcare Using ML and DL approaches: A Case Study -- War Strategy Algorithm based GAN model for Detecting the Malware Attacks in Modern Digital Age -- ML algorithms for providing financial security in banking sectors with the prediction of loan risks -- Machine Learning based DDoS Attack Detection using Support Vector Machine -- Artificial Intelligence based Cyber Security Applications.
520 $a This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications.
650 0 $a Artificial intelligence $x Industrial applications. $3 796380
650 0 $a Computer security. $3 557122
650 0 $a Industry 4.0. $3 1083640
650 1 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Internet of Things. $3 1048478
650 2 4 $a Big Data. $3 1017136
650 2 4 $a Machine Learning. $3 1137723
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Wireless and Mobile Communication. $3 1207058
700 1 $a Sarveshwaran, Velliangiri. $3 1414820
700 1 $a Chen, Joy Iong-Zong. $e editor. $3 1309914
700 1 $a Pelusi, Danilo. $e editor. $3 1314727
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
830 0 $a Advanced technologies and societal change. $3 891386
856 4 0 $u https://doi.org/10.1007/978-981-99-2115-7
950 $a Computer Science (SpringerNature-11645)