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001469766 019__ $$a1382525873
001469766 020__ $$a9789819921157$$q(electronic bk.)
001469766 020__ $$a9819921155$$q(electronic bk.)
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001469766 0247_ $$a10.1007/978-981-99-2115-7$$2doi
001469766 035__ $$aSP(OCoLC)1382693731
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001469766 049__ $$aISEA
001469766 050_4 $$aTA347.A78
001469766 08204 $$a006.3$$223/eng/20230623
001469766 24500 $$aArtificial intelligence and cyber security in Industry 4.0 /$$cVelliangiri Sarveshwaran, Joy Long-Zong Chen, Danilo Pelusi, editors.
001469766 264_1 $$aSingapore :$$bSpringer,$$c[2023]
001469766 264_4 $$c©2023
001469766 300__ $$a1 online resource (viii, 373 pages) :$$billustrations (chiefly color).
001469766 336__ $$atext$$btxt$$2rdacontent
001469766 337__ $$acomputer$$bc$$2rdamedia
001469766 338__ $$aonline resource$$bcr$$2rdacarrier
001469766 4901_ $$aAdvanced technologies and societal change
001469766 5050_ $$aIntro -- Preface -- Contents -- 1 Introduction to Artificial Intelligence and Cybersecurity for Industry -- Introduction -- Classification of Cyberattacks (See Fig. 1.1) -- Types of Cybersecurity -- Tools Used in Cybersecurity -- Firewall -- Honeypots -- How Does Artificial Intelligence Work? (See Fig. 1.3) -- AI Implementation Methods -- Machine Learning -- Deep Learning -- Background Information on AI Methods and Cybersecurity Applications -- The Significance of Cybersecurity -- How AI Can Be Applied on Cybersecurity Issues -- AI Techniques Used for Cybersecurity -- Security Expert Systems
001469766 5058_ $$aDeep Learning Detection for Misinformation -- Benefits of AI in Cybersecurity -- Detecting False Information Using Neural Networks -- Using Neural Networks to Find Objectionable YouTube Content -- Challenges Faced with Integration of AI in Cybersecurity -- Classification Error -- Intensive Requirement for Resources -- Public Perception -- Discussion -- Conclusion -- References -- 2 Role of AI and Its Impact on the Development of Cyber Security Applications -- Introduction -- Overview of Artificial Intelligence -- Literature Survey -- Artificial Intelligence Techniques for Cyber Security
001469766 5058_ $$aVarious Artificial Intelligence Tools and Techniques Are Mentioned Below -- Machine Learning Algorithm Used to Train a Machine -- Why AI is Preferred Over Current Anomaly Detection and Prevention Systems? -- Use Cases of Artificial Intelligence in Cyber Security -- Applications of AI in Cyber Security -- AI Solutions for Cyber Security [26] -- Limitations of AI in Security -- Ethical Issues Related to AI [27] -- AI-Based Threat to Cyber Security [27] -- Conclusion -- References -- 3 AI and IoT in Manufacturing and Related Security Perspectives for Industry 4.0 -- Introduction
001469766 5058_ $$aRole of AI in Manufacturing -- Related Works -- Technologies -- Impact of AI in Manufacturing -- Uses Cases of AI in Manufacturing -- IoT in Manufacturing -- Related Works -- Technologies -- Need of IIoT Security -- Applications -- Vulnerabilities and Challenges -- Quality Control -- Threat Recognition -- Configuration of the Hardware -- Encryption of Data -- Confidentiality of Data -- Integration of Cyber-Physical Systems -- Devices Pairing Key Establishment -- Device Management -- Conclusion and Future Work -- References -- 4 IoT Security Vulnerabilities and Defensive Measures in Industry 4.0
001469766 5058_ $$aIntroduction -- IoT/IIoT Security Challenges and Requirements -- IoT/IIoT Security Challenges -- Requirements for IoT/IIoT Security -- IoT Architecture and Security Attacks -- Architecture of IoT -- IoT Security Attacks in Architectural Perspective -- Preventive Techniques and Mechanisms of IoT/IIoT Security -- Preventive Techniques of IoT Security Attacks -- Mechanisms for Combating IoT/IIoT Security Attacks -- Conclusion -- References -- 5 Adopting Artificial Intelligence in ITIL for Information Security Management-Way Forward in Industry 4.0 -- Introduction -- Definition of AI
001469766 506__ $$aAccess limited to authorized users.
001469766 520__ $$aThis book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications.
001469766 588__ $$aDescription based upon print version of record.
001469766 650_0 $$aArtificial intelligence$$xIndustrial applications.
001469766 650_0 $$aComputer security.
001469766 650_0 $$aIndustry 4.0.
001469766 655_0 $$aElectronic books.
001469766 7001_ $$aSarveshwaran, Velliangiri,$$eeditor.
001469766 7001_ $$aChen, Joy Long-Zong,$$eeditor.
001469766 7001_ $$aPelusi, Danilo,$$eeditor.
001469766 77608 $$iPrint version:$$aSarveshwaran, Velliangiri$$tArtificial Intelligence and Cyber Security in Industry 4. 0$$dSingapore : Springer,c2023$$z9789819921140
001469766 830_0 $$aAdvanced technologies and societal change.
001469766 852__ $$bebk
001469766 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-2115-7$$zOnline Access$$91397441.1
001469766 909CO $$ooai:library.usi.edu:1469766$$pGLOBAL_SET
001469766 980__ $$aBIB
001469766 980__ $$aEBOOK
001469766 982__ $$aEbook
001469766 983__ $$aOnline
001469766 994__ $$a92$$bISE