Apart from technological introduction to deepfakes concept, the book details algorithms to detect deepfakes, techniques for identifying manipulated content and identifying face swap, generative adversarial neural networks, media forensic techniques, deep learning architectures, forensic analysis of deepfakes and so forth.

Loveleen Gaur is the Professor and Program Director (Artificial Intelligence and Business Intelligence and Data Analytics of the Amity International Business School, Amity University, Noida, India. She is senior IEEE member and Series Editor with CRC and Wiley. Prof Gaur is an established Author, Researcher, she has filed five patents and two copyrights in AI-IoT. For over 18 years she served in India and abroad in different capacities. Prof. Gaur has significantly contributed to enhancing scientific understanding by participating in over three hundred scientific conferences, symposia, and seminars, by chairing technical sessions and delivering plenary and invited talks. She has specialized in the fields of Artificial Intelligence, Internet of Things, Data Analytics, Data Mining and Business Intelligence. Prof. Gaur pursued research in truly inter-disciplinary areas and authored and co-authored Books with renowned International and National publishers like Elsevier, Springer, Taylor & Francis. She is invited as Guest Editor for Springer NASA Journal and Emerald Q1 journals. She has published many research papers in SCI and Q1 Journals. She has chaired various positions in International Conferences of repute and is a reviewer with top rated journals of IEEE, SCI and ABDC Journals. Prof Gaur has been invited for AICTE sponsored FDPs and workshops in Industry 4.0, Big Data, Data Analytics and Artificial Intelligence for IITs, NITs and reputed central universities. Prof Gaur is keynote speaker for several IEEE international conferences globally, external examiner/evaluator for PhD, Guest editor of several reputed journals, member of the editorial board of several research journals, and active TPC member of reputed conferences around the globe.

1. Introduction to DeepFake technologies 2. DeepFakes: A Systematic Review and Bibliometric Analysis 3. Deep Learning Techniques for Creation of DeepFakes 4. Analyzing DeepFakes Videos by face warping artifacts 5. Development of image translating model to counter Adversarial attacks 6. Detection of DeepFakes using local features and Convolutional Neural Network 7. DeepFakes: Positive Cases 8. Threats and challenges by DeepFake Technology 9. DeepFakes, media, and societal impacts 10. Fake News Detection using Machine Learning 11. Future of DeepFakes & Ectypes