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    Multimedia Forensics

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    Contributor(s)
    Sencar, Husrev Taha (editor)
    Verdoliva, Luisa (editor)
    Memon, Nasir (editor)
    Language
    English
    Show full item record
    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://library.oapen.org/handle/20.500.12657/54043
    Keywords
    Media Forensics; Digital Image Forensics; Video Forensics; Sensor Noise (PRNU); Deepfakes; Digital Integrity; Video Tampering Detection; Image Tampering Detection; ENF; Counter-Forensics
    DOI
    10.1007/978-981-16-7621-5
    ISBN
    9789811676215, 9789811676215
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Singapore, 2022
    Imprint
    Springer Singapore
    Series
    Advances in Computer Vision and Pattern Recognition,
    Classification
    Computer security
    Image processing
    Computer vision
    Imaging systems and technology
    Machine learning
    Pages
    490
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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