Cyber Security and Operations Management for Industry 4.0
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 8 October 2024
- ISBN 9781032079486
- Binding Paperback
- No. of pages160 pages
- Size 234x156 mm
- Weight 300 g
- Language English
- Illustrations 101 Illustrations, black & white; 29 Halftones, black & white; 72 Line drawings, black & white; 40 Tables, black & white 602
Categories
Short description:
Covering cyber security and Industry 4.0 concepts from a management and operational level, this book connects the topics of Industry 4.0 and cyber security together seamlessly. It discusses both the risks and solutions of using cyber security techniques for Industry 4.0.
MoreLong description:
This book seamlessly connects the topics of Industry 4.0 and cyber security. It discusses the risks and solutions of using cyber security techniques for Industry 4.0.
Cyber Security and Operations Management for Industry 4.0 covers the cyber security risks involved in the integration of Industry 4.0 into businesses and highlights the issues and solutions. The book offers the latest theoretical and practical research in the management of cyber security issues common in Industry 4.0 and also discusses the ethical and legal perspectives of incorporating cyber security techniques and applications into the day-to-day functions of an organization. Industrial management topics related to smart factories, operations research, and value chains are also discussed.
This book is ideal for industry professionals, researchers, and those in academia who are interested in learning more about how cyber security and Industry 4.0 are related and can work together.
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Table of Contents:
Part 1 Cyber Security. 1. Efficient Deep Learning Techniques for Security and Privacy in Industry. 2. Crypto-Based Secure Outbound Supply Chain Authentication for Industry 4.0. 3. A Machine Learning-Based Approach for Fruit Grading and Classification. 4. Artificial Intelligence Impact on Pattern Classification in Association with IoT for Advanced Applications. Part 2 Industry 4.0. 5. A Modified Clonal Selection Algorithm Based on Positive Selection Method in AIS to Solve Job-Shop Scheduling Problem. 6. IoT Health Care Devices for Patient Monitoring, 7. Deep Learning Techniques Used for Detection of Disease in Tomato Plants.
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