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.
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Maße
Höhe: 235 mm
Breite: 191 mm
Gewicht
ISBN-13
978-0-443-38297-0 (9780443382970)
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Schweitzer Klassifikation
Herausgeber*in
School of Computing Engineering and the Built Environment, Edinburgh Napier University, UK
School of Information Science and Technology, Fudan University, China
Prince Sultan University, Saudi Arabia
Professor in Computer Science, Advisor to the Rector, and Leader of the Robotics and Internet of Things Research Lab, Prince Sultan University, Saudi Arabia
School of Computer Science and Informatics, Cyber Technology Institute, De Montfort University, UK
Department of Computer Science, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), Pakistan
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