DeepFakes: Creation, Detection, and Impact
- Length: 148 pages
- Edition: 1
- Language: English
- Publisher: CRC Press
- Publication Date: 2022-09-08
- ISBN-10: 103213920X
- ISBN-13: 9781032139203
- Sales Rank: #0 (See Top 100 Books)
Deepfakes is a synthetic media that leverage powerful AI and ML techniques to generate fake visual and audio content that are extremely realistic and makes it very hard for a human to distinguish from the original ones. 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.
- Provides a technical introduction to deepfakes, its benefits, and the potential harms
- Presents practical approaches of creation and detection of deepfakes using Deep Learning (DL) Techniques
- Draws attention towards various challenging issues and societal impact of deepfakes with their existing solutions
- Includes research analysis in the domain of DL fakes for assisting the creation and detection of deepfakes applications
Discusses future research directions with emergence of deepfakes technology This book is aimed at graduate students, researchers and professionals in data science, artificial intelligence, computer vision, and machine learning.
Cover Half Title Title Page Copyright Page Dedication Table of Contents Preface Acknowledgments Editor Biography Contributors 1 Introduction to DeepFake Technologies 1.1 Introduction 1.2 Demystifying DeepFakes 1.3 Origin and History 1.4 The Growing Trend of DeepFakes 1.5 Why Is It a Matter of Concern? 1.6 How Does DeepFakes Work? 1.6.1 Analyzing the Technology 1.7 Influence of DeepFakes 1.8 Summary References 2 DeepFakes: A Systematic Review and Bibliometric Analysis 2.1 Introduction 2.2 Data Collection 2.2.1 Objective of the Study 2.3 Findings and Discussions 2.3.1 Publication Trends 2.3.2 Co-Authorship to Author 2.3.3 Co-Authorship of Organization 2.3.4 Co-Authorship of Countries 2.3.5 Co-Occurrence of Keywords 2.3.6 Bibliographic Coupling of Authors 2.3.7 List of the Prominent Journals 2.3.8 List of Prominent Conferences 2.4 Discussion 2.5 Summary References 3 Deep Learning Techniques for Creation of DeepFakes 3.1 Introduction 3.2 Cheapfakes vs. DeepFakes 3.2.1 Deep Modeling 3.2.2 Autoencoder 3.2.3 General Adversarial Network 3.3 Applications/Softwares/Programs to Generate DeepFake 3.4 Deep Dive Into Related Papers to Generate Synthetic Media 3.4.1 GAN 3.4.2 Face Swap 3.4.3 Audio 3.4.4 Image Animation 3.5 Summary References 4 Analyzing DeepFakes Videos By Face Warping Artifacts 4.1 Introduction 4.2 Effects of DFs 4.3 DeepFakes Datasets 4.3.1 UADFV 4.3.2 DeepFakes-TIMIT (DF-TIMIT) 4.3.3 FaceForensics ++ 4.3.4 Google DeepFakes Detection—DFD 4.3.5 Facebook DeepFakes Detection Challenge—DFDC 4.3.6 Celeb-DF 4.4 DFs Detection 4.5 Methods of Face-Based Video Manipulation 4.5.1 Temporal Features Across Frames 4.5.1.1 Using Recurrent Neural Networks 4.5.1.2 Eye Blinking 4.5.2 Visual Artifacts Inside Frames 4.5.2.1 Deep Classifiers 4.5.2.2 Shallow Classifiers 4.5.2.3 DeepFakes and Face Manipulations 4.6 Difficulties in Detecting DeepFakes 4.6.1 DeepFake Datasets’ Quality 4.6.2 Evaluation of Performance 4.6.3 Strategies for Identification Have an Absence of Reasonableness 4.6.4 Transient Aggregation 4.6.5 Laundering On Social Media 4.7 Summary References 5 Development of Image Translating Model to Counter Adversarial Attacks 5.1 Introduction 5.2 Related Work 5.3 Datasets 5.4 Data Pre-Processing 5.5 Methodology 5.6 Perturbation 5.7 Gradient 5.8 Result and Discussion 5.8.1 Attack Settings 5.9 Result Analysis 5.10 Summary References 6 Detection of DeepFakes Using Local Features and Convolutional Neural Network 6.1 Introduction 6.2 History of DF 6.3 Applications of DeepFakes 6.4 Advantages of DeepFake 6.5 Disadvantages of DeepFake 6.6 DeepFakes Generation 6.7 DeepFakes Detection Methods 6.8 Local and Global Features of the Image 6.8.1 DeepFakes Detection Using Local Features 6.9 Summary References 7 DeepFakes: Positive Cases 7.1 Introduction 7.2 Applications of DeepFakes 7.2.1 Industry: Healthcare and Pharma 7.2.1.1 Case 7.2.1.2 Case 7.2.1.3 Case 7.2.2 Industry: Retail, E-Commerce, Consulting 7.2.2.1 Case 7.2.3 Industry: Fashion 7.2.3.1 Case 7.2.3.2 Case 7.2.4 Industry: Media and Entertainment 7.2.4.1 Case 7.2.4.2 Case 7.2.4.3 Case 7.2.5 Industry: Education 7.2.5.1 Case 7.3 Summary References 8 Threats and Challenges By DeepFake Technology 8.1 Introduction 8.2 DFs and Their Growth 8.3 Threat of DFs 8.4 Threats to National Security 8.5 Threat to Individuals 8.6 Threat to Society 8.7 Threats to Judicial Systems 8.8 Threats to Politics Or Democratic Discourse 8.9 Threat to Elections 8.10 Threats to Businesses 8.11 The Threat in Corroding Trust in Institutions 8.12 Countermeasures 8.13 Legislative Measures 8.14 Technological Countermeasures 8.15 Summary References 9 DeepFakes, Media, and Societal Impacts 9.1 Introduction 9.2 A Shortage of Experimental Inquire About 9.3 A Few Bits of Knowledge From Double-Dealing Investigate 9.4 Societal Impact 9.5 Summary References 10 Fake News Detection Using Machine Learning 10.1 Introduction 10.2 Reasons Using Social Media for Fake News 10.3 Reasons to Spread Fake News 10.4 Venomous Accounts On Social Media for Advocacy 10.5 Fake News Detection Methods 10.6 Linear Regression 10.7 Random Forest 10.8 Decision Tree 10.9 Gradient Boosting Classifier 10.10 Passive-Aggressive Classifier 10.11 Related Work 10.12 Objective 10.13 Methodology 10.14 Dataset 10.15 Data Pre-Processing 10.16 Model Evaluation 10.17 Result and Discussions 10.18 Summary References 11 Future of DeepFakes and Ectypes 11.1 Introduction 11.2 DeepFakes and Reality 11.3 Forgery and Ectypes 11.4 Image Forgery Detector With DeepFakes 11.5 Legal Issues With DeepFakes and Future Strategies (Property Rights) 11.6 Future Strategies: Through Organizational Aspects 11.7 Future Strategies: Through Societal Aspects 11.8 Future Strategies: Through Governmental Aspects 11.9 Social Media: A Fuel to Forged Content? 11.10 Combating With a “Pre-Ready Response” 11.11 Legal System and Policies (Across Different Nations) 11.12 Is DeepFakes Here to Stay Or Not?/Future Forecast 11.13 Future Expectations From DeepFake References Index
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