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Artificial Intelligence and Cyber Security in Industry 4.0

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 l...

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Detalhes bibliográficos
Autor Corporativo: SpringerLink (Online service)
Outros Autores: Sarveshwaran, Velliangiri (Editor), Chen, Joy Iong-Zong (Editor), Pelusi, Danilo (Editor)
Formato: Recurso Electrónico livro electrónico
Idioma:inglês
Publicado em: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edição:1st ed. 2023.
Colecção:Advanced Technologies and Societal Change,
Assuntos:
Artificial intelligence.
Internet of things.
Big data.
Machine learning.
Computational intelligence.
Wireless communication systems.
Mobile communication systems.
Artificial Intelligence.
Internet of Things.
Big Data.
Machine Learning.
Computational Intelligence.
Wireless and Mobile Communication.
Acesso em linha:https://doi.org/10.1007/978-981-99-2115-7
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Sumário:
  • 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.

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