Deepfakes 2.0: Creation, Detection, and the Future of Synthetic Media
暫譯: Deepfakes 2.0：生成、偵測與合成媒體的未來
Gaur, Loveleen
- 出版商: CRC
- 出版日期: 2026-11-30
- 售價: $6,080
- 貴賓價: 9.5 折 $5,776
- 語言: 英文
- 頁數: 222
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 104125380X
- ISBN-13: 9781041253808
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相關分類:
Computer Vision、DeepLearning、GAN 生成對抗網絡
尚未上市，無法訂購
相關主題
商品描述
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.
商品描述(中文翻譯)
本書以跨學科方式探討合成媒體（synthetic media），結合技術洞見與全球案例研究，涵蓋《EU AI Act》、美國《DEEPFAKES Accountability Act》，以及中國的深度合成治理框架。更新後的章節涵蓋多模態合成、即時偵測、對抗式強健性，以及 AI 可解釋性工具。本書分為四個部分，分別探討基礎概念、進階技術、社會影響與未來趨勢。
• 不僅探討臉部替換，還涵蓋語音複製、跨模態合成與擴散模型，使本書成為目前最即時、最完整的合成媒體學術參考書之一。
• 說明現有與新興的偵測策略，包括以 CNN 為基礎的方法、對抗式訓練、浮水印技術與可解釋性工具。
• 涵蓋持續演進的法律與監管標準，例如 C2PA 規範、同意框架與數位身分治理，為政策討論提供具時效性的參考。
• 討論全球治理方法、合成媒體的建設性應用，以及使技術與監管具備未來適應力的發展藍圖。
• 收錄新的全球與區域案例研究，包括《EU AI Act》、美國《DEEPFAKES Accountability Act》、中國的深度合成法規、印度《IT Act》的修正案、非洲 AI 倫理框架，以及由 UNESCO 與 UNDP 支持的中東和非洲倡議。
本書適合資料科學、人工智慧、電腦視覺、機器學習與電腦科學領域的研究生、研究人員及專業人士閱讀。
作者簡介
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.
作者簡介(中文翻譯)
Loveleen Gaur 是人工智慧、統計學與資料科學領域的教師學者，在四大洲累積超過二十年的大學教學、研究、學術領導與課程建置經驗。她的研究重點包括 AI 倫理與治理、可解釋 AI、負責任 AI、生成式 AI、醫療 AI、醫學影像、預測分析，以及 AI 政策與法規。她目前擔任多項國際學術與專業職務，包括印度 Bengaluru Alliance University 的研究教授；美國 San Francisco Golden Gate University Worldwide DBA 課程的論文委員會主席；斐濟 University of the South Pacific 的兼任教授；秘魯 Lima Universidad Nacional Mayor de San Marcos 深度科技（Deep Tech）：AI 與新興科技博士課程的學術領導；Paris School of Business 的實務教授；upGrad 的主題專家；英國 Innovate UK、UK Research and Innovation 的評審；以及 QS Reimagine Education Awards 2026 的評審。她過去曾任職於印度 Noida 的 Amity University，並在該校創立人工智慧與商業分析研究所課程。
她已撰寫及編輯超過二十本研究專書，發表超過 150 項研究成果，累積超過 4,500 次引用，並在各大出版社與學術期刊完成超過 170 次經認證的同儕審查。她入選 Elsevier-Stanford 2024 年與 2025 年全球前 2% 頂尖科學家名單，並為 IEEE 資深會員。她的研究成果曾發表於 Frontiers in Neuroscience、Information Sciences、Multimedia Systems，以及 ACM Transactions on Multimedia Computing, Communications, and Applications 等期刊。
她的編輯領導經驗包括擔任 Taylor & Francis 出版之 Communications in Statistics: Case Studies, Data Analysis and Applications 的共同主編。她也曾擔任多本 Frontiers 期刊的主題編輯與客座編輯，並透過廣泛參與同儕審查、發表主題演講、指導博士生、審查論文，以及參與國際學術合作，為全球研究社群貢獻心力。
