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            Multimedia Forensics

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            Contributor(s)
            Sencar, Husrev Taha (editor)
            Verdoliva, Luisa (editor)
            Memon, Nasir (editor)
            Language
            English
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            Abstract
            This book is open access. Media forensics has never been more relevant to societal life. Not only media content represents an ever-increasing share of the data traveling on the net and the preferred communications means for most users, it has also become integral part of most innovative applications in the digital information ecosystem that serves various sectors of society, from the entertainment, to journalism, to politics. Undoubtedly, the advances in deep learning and computational imaging contributed significantly to this outcome. The underlying technologies that drive this trend, however, also pose a profound challenge in establishing trust in what we see, hear, and read, and make media content the preferred target of malicious attacks. In this new threat landscape powered by innovative imaging technologies and sophisticated tools, based on autoencoders and generative adversarial networks, this book fills an important gap. It presents a comprehensive review of state-of-the-art forensics capabilities that relate to media attribution, integrity and authenticity verification, and counter forensics. Its content is developed to provide practitioners, researchers, photo and video enthusiasts, and students a holistic view of the field.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/198710
            Keywords
            Media Forensics; Digital Image Forensics; Video Forensics; Sensor Noise (PRNU); Deepfakes; Digital Integrity; Video Tampering Detection; Image Tampering Detection; ENF; Counter-Forensics; thema EDItEUR::U Computing and Information Technology::UR Computer security; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQV Computer vision; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TT Other technologies and applied sciences::TTB Applied optics::TTBM Imaging systems and technology; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
            DOI
            10.1007/978-981-16-7621-5
            ISBN
            9789811676215
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Singapore, 2022
            Imprint
            Springer Singapore
            Series
            Advances in Computer Vision and Pattern Recognition,
            Pages
            490
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            • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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