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Artificial Intelligence and Cyber Security in Industry 4.0 / edited by Velliangiri Sarveshwaran, Joy Iong-Zong Chen, Danilo Pelusi
(Advanced Technologies and Societal Change. ISSN:21916861)

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
大きさ	VIII, 373 p. 100 illus., 86 illus. in color : online resource
著者標目	Sarveshwaran, Velliangiri editor Chen, Joy Iong-Zong editor Pelusi, Danilo editor SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002810	Computer Scinece R0 2005-6,2022-3				9789819921157

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一般注記	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 HTTP:URL=https://doi.org/10.1007/978-981-99-2115-7
件　名	LCSH:Artificial intelligence LCSH:Internet of things LCSH:Big data LCSH:Machine learning LCSH:Computational intelligence LCSH:Wireless communication systems LCSH:Mobile communication systems FREE:Artificial Intelligence FREE:Internet of Things FREE:Big Data FREE:Machine Learning FREE:Computational Intelligence FREE:Wireless and Mobile Communication
分　類	LCC:Q334-342 LCC:TA347.A78 DC23:006.3
書誌ID	EB00002198
ISBN	9789819921157