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Real, Forged or Deep Fake? Enabling the Ground Truth on the Internet

Mohammad A. Hoque, Md Sadek Ferdous, Mohsin Khan, Sasu Tarkoma

2021IEEE Access13 citationsDOIOpen Access PDF

Abstract

The proliferation of smartphones and mobile communication has enabled users to capture images or videos and share them immediately on social networking and messaging platforms. These platforms are also used to manipulate the masses by performing social engineering attacks by sharing fabricated images (or videos). These attacks cause public shame, ethnic violence, and claim lives. With the rise of advanced image processing tools, the deep fakes are automated, and their implications are boundless. In this article, we discuss different types of modification of images/videos and survey the corresponding methods and tools. We also highlight the ongoing efforts to detect fake images and videos using advanced machine learning tools and fact-checking. Along with these tools, we also need different complementary approaches discouraging the production and propagation of manipulative forged images and videos on the Internet. This paper further emphasizes that we desperately need socio-technological solutions that empower end users with the right tools to make an informed moral decision while producing, uploading, and sharing media. Finally, supporting this, we discuss a holistic blockchain-based solution.

Topics & Concepts

UploadComputer scienceThe InternetSocial mediaShameCybercrimeInternet privacyMobile deviceAdversarial systemCyberspaceDeep learningWorld Wide WebComputer securityHuman–computer interactionArtificial intelligenceMultimediaPolitical scienceLawAdversarial Robustness in Machine LearningMisinformation and Its ImpactsGenerative Adversarial Networks and Image Synthesis
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