Machine Learning and Deep Learning Driven Techniques for Multimodal Data Security in the Internet of Multimedia Things

Sita Rani is an assistant professor at Guru Nanak Dev Engineering College, Ludhiana, India, and a postdoctoral research scientist at the University of South Florida, USA. She earned her PhD in Computer Science and Engineering from I.K. Gujral Punjab Technical University, India, in 2018 and completed her postdoctoral research at South Ural State University, Russia (2022-23). She also holds a PG certificate in Data Science and Machine Learning from IIT Roorkee. With over 23 years of academic and research experience, she has been recognized among Stanford University's Top 2% Scientists (2024, 2025). She has received the ISTE Best Teacher Award (2020) and the International Young Scientist Award (2021). Her work includes SCIE/Scopus publications, patents, books, and contributions to AI, data science, healthcare, and sustainability.Sachin Kumar is an associate professor and researcher in the Akian College of Science and Engineering at the American University of Armenia (AUA), Yerevan, Armenia, since July 2024, and is currently serving as vice chair of IEEE Armenia subsection. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a life member of the International Association of Engineers (IAENG), and a member of the Association for Computing Machinery (ACM). He is an associate editor of various indexed journals published by the IET, Wiley, Elsevier, and Nature. His research interests include AI and its applications to smart environments, Internet of Things, natural language processing, and cognitive sciences. He is the author of 90+ scientific articles published in peer-reviewed journals indexed in Web of Science (WoS) and Scopus. He earned his PhD degree in Data Mining from IIT Roorkee, India.

• Chapter 1: Introduction to multimodal dataChapter 2: Role of multimedia systems and tools in diversified domainsChapter 3: Internet of Multimedia Things: key role, framework, and security issuesChapter 4: Challenges in the adoption of ML and DL techniques for securing multimodal dataChapter 5: Analysis and management of multimodal data: big data approachChapter 6: Security issues and mechanisms in multimodal dataChapter 7: ML and DL techniques to detect cyberattacks on multimodal databasesChapter 8: Privacy-preserving ML to safeguard multimodal data: Internet of Multimedia Things frameworkChapter 9: Deep learning with blockchain to deploy secure multimodal smart city applicationsChapter 10: Secure ML and DL systems for intelligent traffic monitoring and managementChapter 11: Security of multimodal healthcare data: importance, techniques, and challengesChapter 12: ML facilitated encrypted smart home systems in the Internet of Multimedia ThingsChapter 13: Machine learning with blockchain for securing agriculture-based applicationsChapter 14: Leveraging ML and DL for safeguarding multimodal data in Industrial IoT environmentsChapter 15: Safeguarding educational multimodal data in the IoT with ML and DLChapter 16: Conclusions