Internet of Multimedia Things Security
Tools and Applications
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Product details:
- Publisher Elsevier
- Date of Publication 23 January 2026
- ISBN 9780443328848
- Binding Paperback
- No. of pages350 pages
- Size 235x191 mm
- Language English 700
Categories
Long description:
The proliferation of IoT devices and the exponential growth of multimedia brings opportunities and challenges. IoMT has uses in a variety of fields, including healthcare, education, agriculture, communication and entertainment, but IoMT networks are susceptible to security issues that must be addressed. Internet of Multimedia Things Security: Tools and Applications introduces the principles behind the IoMT by exploring three converging three domains: Internet of Things, Data Security, and Multimedia. It covers vulnerabilities such as cyber-attacks, unauthorized access, data breaches, and privacy preservation, and provides case studies to assist research students and engineers in securely incorporate multimedia into their applications.
- Offers a comprehensive understanding of the foundational principles of the Internet of Multimedia Things and its practical applications in IoT
- Provides practical applications and case studies in the application of IoMT security
- Discusses the ethical implications in IoMT engineering
- Investigates the possibilities and challenges of utilising emerging technologies, such as federated learning, explainable AI and Adversarial, in IoMT security
Table of Contents:
1. Introduction to IoMT Security and Challenges
2. Multimedia Data Handling in IoMT
3. IoT Hardware Security in IoMT
4. Secure Communication Protocols for Multimedia Things in IoMT
5. IoMT Authentication and Authorization
6. Intrusion Detection and Prevention Systems (IDPS) for IoMT
7. Multimedia Data Security in IoMT
8. Privacy in IoMT
9. IoMT Cloud Security Issues and Countermeasures
10. Multimedia Forensics in IoMT: Techniques and Applications
11. Case Studies on Security Implementations in IoMT
12. Future Trends and Emerging Technologies in IoMT Security
13. Federated Learning applications for IoMT Security
14. Explainable AI for IoMT Security
15. Adversarial ML for IoMT security
