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

Inbunden, Engelska, 2026

Del i serien Security

1 725 kr

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Beskrivning

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.The internet of multimedia things (IoMT) is one of the key contributors to the collection, analysis and management of voluminous multimodal data. The dominating features of IoMTs are well-timed delivery of data and dependability, but they require high levels of memory and computational power, which requires higher bandwidth and more power. Therefore, they require rigorous quality of service (QoS) and efficient, reliable and secure network frameworks.The objective of this book is to explore machine learning (ML) and deep learning (DL) techniques for securing data with multiple modalities in a wide range of data-centric smart applications in the IoMT framework. In all data-centric application domains where on-time availability of data and reliability are the major concerns, IoMT is contributing significantly. The authors present the challenges faced to organize and process multimodal data in data-centric applications, several types of data modalities, and innovative IoMT frameworks. A particular focus is placed on the role of ML and DL techniques in securing multi-modal data for real-time monitoring in smart environment applications.Machine Learning and Deep Learning Driven Techniques for Multimodal Data Security in the Internet of Multimedia Things caters to the needs of AI, big data and IoT advanced students, academic and industry researchers, engineers, security experts, data analysts, and AI and data-centric application developers.

Produktinformation

Utgivningsdatum:2026-09-01
Mått:156 x 234 x undefined mm
Format:Inbunden
Språk:Engelska
Serie:Security
Antal sidor:256
Förlag:Institution of Engineering and Technology
ISBN:9781837241354

Utforska kategorier

Databaser inom Data och IT
Systemvetenskap och AI inom Data och IT

Mer om författaren

Sita Rani is a postdoctoral research scientist at the University of South Florida, USA, and also serves at Guru Nanak Dev Engineering College, Ludhiana, India. With over 23 years of academic and research experience, she has been recognised 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).

Innehållsförteckning

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 Cyber Attacks 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 Homes Systems in the Internet of Multimedia EnvironmentChapter 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 DL