
Edge Intelligence
Advanced Deep Transfer Learning for IoT Security
Syngress (Publisher)
Will be published approx. on 1. January 2026
Book
Paperback/Softback
280 pages
978-0-443-38297-0 (ISBN)
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.
More details
Language
English
Place of publication
United States
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 191 mm
Weight
450 gr
ISBN-13
978-0-443-38297-0 (9780443382970)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jawad Ahmad | Shahid Latif MSc | Wadii Boulila
Edge Intelligence
Advanced Deep Transfer Learning for IoT Security
E-Book
01/2026
Elsevier
€166.99
Available for download
Persons
Editor
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
Content
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
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