DeepFakes 2.0

Creation, Detection, and the Future of Synthetic Media
2 ed
ISBN: 978-1-041-25380-8
Verlag: Taylor & Francis Ltd

Buch, Englisch, 238 Seiten, Format (B × H): 156 mm x 234 mm

Deepfakes and synthetic media have moved well beyond face swaps. This second edition offers an interdisciplinary examination of how synthetic media is created, detected, and governed, combining technical depth with global case studies. Organized into four parts covering foundations, advanced techniques, societal impact, and future directions, it has been updated throughout to reflect advances in multimodal generation, real-time detection, and adversarial robustness.

- Covers the full generative landscape, including voice cloning, cross-modal synthesis, and diffusion models, alongside established face-swap methods

- Explains detection strategies from CNN-based classifiers to newer architectures, with attention to adversarial robustness, generalization to unseen generators, and explainability tools

- Examines provenance and authentication approaches, including watermarking and the C2PA Content Credentials standard, together with consent frameworks and digital identity governance

- Compares regulatory responses worldwide, including the EU AI Act's transparency obligations, US federal and state legislation and proposals, China's deep synthesis provisions, India's IT Rules on synthetic content, the African Union's Continental AI Strategy, and UNESCO- and UNDP-supported initiatives in the Middle East and Africa

- Highlights constructive applications of synthetic media and offers a roadmap for future-proofing both technology and regulation

This book is intended for graduate students, researchers, and professionals in artificial intelligence, computer vision, machine learning, and data science, as well as policymakers, legal scholars, and trust and safety practitioners working on digital media integrity.

Zielgruppe

Academic, Postgraduate, and Professional Reference

Autoren/Hrsg.

Gaur, Loveleen

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung

Inhaltsverzeichnis

1.Introduction to DeepFake Technologies 2. Anatomy of a Deepfake: A Taxonomy of Synthetic Media 3.Deep Learning Techniques for the Creation of DeepFakes 4. Analyzing DeepFakes Videos by Face Warping Artifacts 5: Development of an Image-Translating Model to Counter Adversarial Attacks 6: Multimodal Deepfakes and the Evolution of Generative Models: From Cross-Modal Synthesis to Diffusion Architectures 7: Deepfake Detection in Real-Time Adversarial Environments: Architectures, Threat Models, and Deployment Strategies 8: Fairness, Bias, and Explainability in Detection AI 9: DeepFakes, Media, and Societal Impacts 10: Fake News Detection Using Machine Learning 11: Legal, Ethical, and Governance Perspectives on Deepfakes 12: Constructive Applications for DeepFakes: Educational Tools, Cybersecurity, and Digital Immortality 13: Societal Impact of DeepFakes 14: Global Regulatory Landscapes for Deepfakes: A Comparative Review of the EU, US, China, and India

Über Autor(innen)

Loveleen Gaur is a teacher-scholar in artificial intelligence, statistics, and data science with more than twenty years of university teaching, research, academic leadership, and curriculum-building experience across four continents. Her work focuses on AI ethics and governance, explainable AI, responsible AI, generative AI, healthcare AI, medical imaging, predictive analytics, and AI policy and regulation. She is currently associated with several international academic and professional roles, including Research Professor at Alliance University, Bengaluru, India; Dissertation Committee Chair in the DBA Program at Golden Gate University Worldwide, San Francisco, USA; Adjunct Professor at the University of the South Pacific, Fiji; Faculty Lead for the Doctoral Program in Deep Tech: AI and Emerging Technologies at Universidad Nacional Mayor de San Marcos, Lima, Peru; Professor of Practice with Paris School of Business; Subject Matter Expert with upGrad; Assessor with Innovate UK, UK Research and Innovation; and Judge for the QS Reimagine Education Awards 2026. She previously served as Professor at Amity University, Noida, India, where she founded postgraduate programs in Artificial Intelligence and Business Analytics.

She has authored and edited more than twenty research books and has over 150 research outputs, more than 4,500 citations, and over 170 verified peer reviews across leading publishers and journals. She has been recognized in the Elsevier-Stanford list of the World's Top 2% Scientists for 2024 and 2025 and is a Senior Member of IEEE. Her publications have appeared in journals such as Frontiers in Neuroscience, Information Sciences, Multimedia Systems, and ACM Transactions on Multimedia Computing, Communications, and Applications.

Her editorial leadership includes serving as Co-Editor-in-Chief of Communications in Statistics: Case Studies, Data Analysis and Applications, published by Taylor & Francis. She has also contributed as a topic and guest editor across Frontiers journals and has served the global research community through extensive peer review, keynote talks, doctoral supervision, thesis examination, and international academic collaborations.