We are living in an AI and data-driven era. A huge volume of data is generated from all sectors including smart cities, intelligent transportation systems, smart healthcare, education, smart agriculture and smart industrial processes. This information comprises multiple modalities such as textual data, images, sound, gestures and genetic sequences, which are generated through various sources.

• Chapter 1: Introduction to Multimodal Data
• Chapter 2: Role of Multimedia Systems and tools in Diversified Domains
• Chapter 3: Internet of Multimedia Things: Key Role, Framework, and Security Issues
• Chapter 4: Challenges in the Adoption of ML and DL Techniques for Securing Multimodal Data
• Chapter 5: Analysis and Management of Multimodal Data: Big Data Approach
• Chapter 6: Security Issues and Mechanisms in Multimodal Data
• Chapter 7: ML and DL Techniques to Detect Cyber Attacks on Multimodal Databases
• Chapter 8: Privacy-Preserving ML to Safeguard Multimodal Data: Internet of Multimedia Things Framework
• Chapter 9: Deep Learning with Blockchain to Deploy Secure Multimodal Smart City Applications
• Chapter 10: Secure ML and DL Systems for Intelligent Traffic Monitoring and Management
• Chapter 11: Security of Multimodal Healthcare Data: Importance, Techniques, and Challenges
• Chapter 12: ML Facilitated Encrypted Smart Homes Systems in the Internet of Multimedia Environment
• Chapter 13: Machine Learning with Blockchain for Securing Agriculture-based Applications
• Chapter 14: Leveraging ML and DL for Safeguarding Multimodal Data in Industrial IoT Environments
• Chapter 15: Safeguarding Educational Multimodal Data in the IoT with ML and DL