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  • Edge Intelligence: Advanced Deep Transfer Learning for IoT Security

    Edge Intelligence by Ahmad, Jawad; Latif, Shahid; Boulila, Wadii;

    Advanced Deep Transfer Learning for IoT Security

      • GET 10% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 166.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        69 259 Ft (65 961 Ft + 5% VAT)
      • Discount 10% (cc. 6 926 Ft off)
      • Discounted price 62 333 Ft (59 365 Ft + 5% VAT)

    69 259 Ft

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    Availability

    Not yet published.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Elsevier Science
    • Date of Publication 1 January 2026

    • ISBN 9780443382970
    • Binding Paperback
    • No. of pages280 pages
    • Size 235x191 mm
    • Weight 450 g
    • Language English
    • 700

    Categories

    Long description:

    Edge Intelligence: Advanced Deep Transfer Learning for IoT Security presents a comprehensive exploration into the critical intersection of cybersecurity, edge computing, and deep learning, offering practitioners, researchers, and cybersecurity professionals a definitive guide to protect IoT/IIoT systems. This book delves into the synergistic potential of edge computing and advanced machine/deep learning algorithms, providing insights into lightweight and resource-efficient models with a special focus on resource-constrained edge devices. The rapidly evolving nature of cyberattacks underscores the need for updated and integrated resources that address the intersection of cybersecurity, edge computing, and deep learning. The authors address this issue by offering practical insights, lightweight models, and proactive defense mechanisms tailored to the unique challenges of securing edge devices and networks. This book is not only written to provide its audience effective strategies to detect and mitigate network intrusions by leveraging edge intelligence and advanced deep transfer learning techniques but also to provide practical insights and implementation guidelines tailored to resource-constrained edge devices.

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    Table of Contents:

    1. Introduction to IoT and IIoT Security
    2. Fundamentals of Deep Learning and Transfer Learning
    3. Edge Computing: Architecture and Security
    4. Deep Transfer Learning for Intrusion and Anomaly Detection
    5. Resource-Efficient Models for Edge Devices
    6. Secure Communication and Privacy-Preserving Techniques in Edge Intelligence
    7. Case Studies and Industry Applications
    8. Future Trends and Emerging Technologies in IoT Security
    9. Developing and Implementing a Comprehensive IoT Security Strategy
    10. Conclusion

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