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It is our great pleasure to welcome you to the first ACM Workshop on the security implications of Deepfakes and Cheapfakes - WDC 2022, co-located with ACM AsiaCCS 2022. The workshop's mission is to share and discuss novel solutions to the security and privacy-related issues that arise from fake multimedia. A total of ten papers were submitted in response to the call for papers, with authors from four countries: Germany, Israel, South Korea, and the United States. The submissions' significance, novelty, technical quality, and field relevance were all considered. The review process was conducted in a double-blind fashion. The program committee members exerted considerable effort in evaluating the papers, with the majority receiving two or three reviews. Finally, we accepted four short papers with a 57.1% acceptance rate and three poster papers for presentation at the workshop.

Deepfakes.

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This study deals with the growing trend of Russia's use of historical propaganda to further its foreign policy goals. It contains chapters written by experts in the field in the respective countries of Estonia, Finland, Latvia and Poland. The methodological aspects of the project were discussed in detail during a seminar in Riga on 11 December 2018. It was agreed that, for the integrity of the compendium, at least the central theme should be commonly understood as Jowett and O'Donnell conceptualise it: propaganda is a deliberate and systematic attempt to shape perceptions, manipulate cognitions, and direct behaviour to achieve a response that furthers the desired intent of the propagandist. Its systematic nature requires the longitudinal study of its progress. Because the essence of propaganda is its deliberateness of purpose, considerable investigation is required to find out what this purpose is.

Propaganda. --- Disinformation. --- Deepfakes.

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Deepfakes is a synthetic media that leverage powerful Artificial Intelligence (AI) and machine learning (ML) techniques to generate fake visual and audio content that are extremely realistic, thus making it very hard for a human to distinguish from the original ones. Apart from technological introduction to the 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 harmsPresents practical approaches of creation and detection of DeepFakes using Deep Learning (DL) TechniquesDraws attention towards various challenging issues and societal impact of DeepFakes with their existing solutionsIncludes research analysis in the domain of DL fakes for assisting the creation and detection of DeepFakes applicationsDiscusses future research directions with emergence of DeepFakes technologyThis book is aimed at graduate students, researchers and professionals in data science, artificial intelligence, computer vision, and machine learning.

Deepfakes. --- Disinformation --- Disinformation --- Prevention. --- Social aspects.

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From deepfakes to GPT-3, deep learning is now powering a new assault on our ability to tell what's real and what's not, bringing a whole new algorithmic side to fake news. On the other hand, remarkable methods are being developed to help automate fact-checking and the detection of fake news and doctored media. Success in the modern business world requires you to understand these algorithmic currents, and to recognize the strengths, limits, and impacts of deep learning---especially when it comes to discerning the truth and differentiating fact from fiction. This book tells the stories of this algorithmic battle for the truth and how it impacts individuals and society at large. In doing so, it weaves together the human stories and what's at stake here, a simplified technical background on how these algorithms work, and an accessible survey of the research literature exploring these various topics. How Algorithms Create and Prevent Fake News is an accessible, broad account of the various ways that data-driven algorithms have been distorting reality and rendering the truth harder to grasp. From news aggregators to Google searches to YouTube recommendations to Facebook news feeds, the way we obtain information today is filtered through the lens of tech giant algorithms. The way data is collected, labelled, and stored has a big impact on the machine learning algorithms that are trained on it, and this is a main source of algorithmic bias which gets amplified in harmful data feedback loops. Dont be afraid: with this book youll see the remedies and technical solutions that are being applied to oppose these harmful trends. There is hope.

Fake news --- Deepfakes --- Computer algorithms. --- Prevention. --- Algorithms --- Deep fakes --- Deepfake AI --- Disinformation --- Forgery --- News, Fake --- Hoaxes --- Journalism --- Social media. --- User-generated media --- Communication --- User-generated content

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This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area.

Biometric identification. --- Deepfakes. --- Image processing --- Morphing (Computer animation). --- Digital techniques. --- Biometric person authentication --- Biometrics (Identification) --- Anthropometry --- Identification --- Computer-generated metamorphosis --- Metamorphosing (Computer animation) --- Computer animation --- Digital image processing --- Digital electronics --- Deep fakes --- Deepfake AI --- Disinformation --- Forgery --- DeepFakes --- Face Manipulation Detection --- Media Forensic --- Biometric Recognition --- Image Processing and Pattern Recognition --- Open Access