Generative AI for Multimedia Content Processing, Security and Privacy
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Generative AI for Multimedia Content Processing, Security and Privacy

Generative AI for Multimedia Content Processing, Security and Privacy


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About the Book

Exploring the field of generative artificial intelligence (GenAI) and its use in the processing and security of multimedia content, this co-authored book addresses the critical needs and emerging challenges in the rapidly evolving intersection of artificial intelligence, multimedia content, and cybersecurity. The capabilities of sophisticated GenAI models in generating, improving, and manipulating multimedia information, including images, videos, and audio are thoroughly explored. Coverage also extends to technical innovations including advanced neural network topologies, novel training methods, and methods for boosting GenAI-generated content quality and authenticity.

The book's focus on security and privacy concerns and the weaknesses brought on by GenAI includes data privacy challenges, the development of unlicensed material, and the exploitation of AI for nefarious intentions. Furthermore, the ethical implications and legal obstacles involved in guaranteeing the secure and accountable implementation of generative AI in multimedia applications are examined and potential future directions identified.

Generative AI for Multimedia Content Processing, Security and Privacy: Fundamentals, advances and applications will be a useful reference for multimedia researchers and engineers working with GenAI, particularly those interested in security and privacy challenges. Cybersecurity researchers and engineers working on digital content security and synthetic media prevention, AI researchers and engineering and technology practitioners developing generative AI technologies, will all find relevant information in this volume. The book will also be of interest to regulatory and compliance experts, policy makers and regulators working on AI deployment and data protection; and digital rights and intellectual property specialists.



Table of Contents:
  • Chapter 1: Introduction to Generative AI for Multimedia Content Processing
  • Chapter 2: Technical Foundations of Generative AI
  • Chapter 3: Generative AI for Image and Video Processing
  • Chapter 4: Generative AI for Audio and Speech Processing
  • Chapter 5: Ethical and Regulatory Perspectives of Generative AI
  • Chapter 6: Risk Assessment and Management of Generative AI Systems
  • Chapter 7: Security Challenges and Innovative Solutions for Generative AI
  • Chapter 8: Privacy-Preserving Techniques and Mitigation Strategies for Generative AI
  • Chapter 9: Case Studies and Real-World Applications in Generative AI
  • Chapter 10: Generative AI Collaborative Approaches and Open-Source Initiatives
  • Chapter 11: Future Trends in Generative AI


About the Author :
Surjeet Dalal is a researcher and professor in the Department of Computer Science and Engineering at Amity University Haryana, India. He has over 18 years of teaching and research experience. His expertise spans Artificial Intelligence, Cybersecurity, IoT, Machine Learning, and Industry 5.0. He has published over 100 SCI and Scopus-indexed papers, authored six books, filed fourteen patents, and is a member of the International Association of Engineers (IAENG). Umesh Kumar Lilhore is a researcher in the Department of Computer Science and Engineering at Galgotias University, India. With a PhD, postdoctoral degree, and over 100 publications in top-tier journals, his research spans AI, machine learning, and computer security. A senior IEEE member, he has authored five books, holds 20 patents, and serves as an editor for Springer BMC Medical Informatics and Decision Making. Shalini Bhaskar Bajaj is a researcher, professor and head of the Department of Computer Science and Engineering at Amity University Haryana, India. Her research focuses on artificial intelligence, machine learning and data analytics. She has published over 100 research papers in SCI and Scopus peer reviewed journals. She is editor-in-chief of the Journal of Data Science and Cybersecurity (JDSCS). She is fellow of the Institution of Engineers (India) (FIE) and also member of the International Association of Engineers (IAENG). Momina Shaheen is a senior lecturer in computing at the University of Roehampton, London, UK. She has led several projects in the areas of artificial intelligence, machine learning, data science, agent-based modelling, cognitive sciences and distributed systems. She has published 35+ research papers in computing and cutting-edge technologies and has authored 2 books.


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Product Details
  • ISBN-13: 9781837242092
  • Publisher: Institution of Engineering and Technology
  • Publisher Imprint: Institution of Engineering and Technology
  • ISBN-10: 1837242097
  • Publisher Date: 01 Mar 2026


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