This book offers an interdisciplinary exploration of synthetic media, combining technical insights with global case studies, including the EU AI Act, the U.S. DEEPFAKES Accountability Act, and China's deep synthesis governance frameworks. Updated chapters cover multimodal synthesis, real-time detection, adversarial robustness, and AI explainability tools. Organized into four sections, the book examines foundational concepts, advanced techniques, societal impacts, and future trends. Goes beyond face swaps to include voice cloning, cross-modal synthesis, and diffusion models, making it one of the most up-to-date academic references on synthetic media. Explains current and emerging detection strategies, including CNN-based approaches, adversarial training, watermarking techniques, and explainability tools. Covers evolving legal and regulatory standards, such as C2PA specifications, consent frameworks, and digital identity governance, providing timely relevance for policy discussions. Discusses global governance approaches, constructive applications of synthetic media, and a roadmap for future-proofing technology and regulation. Includes new global and regional case studies, such as the EU AI Act, the U.S. DEEPFAKES Accountability Act, China's deep synthesis regulations, amendments to India's IT Act, African AI ethics frameworks, and UNESCO- and UNDP-backed initiatives in the Middle East and Africa. This book is intended for graduate students, researchers, and professionals in data science, artificial intelligence, computer vision, machine learning, and computer science.
