Deepfakes and the New Disinformation War

By D. Citron, R. Chesney. 2018

283 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/62045fcbd71150aaba97a9166ca00f38e38c3932

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Citations in the corpus

Deep learning for deepfakes creation and detection: A survey (2019, background): “videos of world leaders with fake speeches for falsification purposes [9], [10].”
Deepfakes: Trick or treat? (2020, unknown): “Providing this data is referred to as an ‘alibi service’ or a ‘life log’ (Chesney & Citron, 2019).”
Watch Your Up-Convolution: CNN Based Generative Deep Neural Networks Are Failing to Reproduce Spectral Distributions (2020, background): “The term deepfake [22, 8] describes the recent phenomenon of people misusing advances in artificial face generation via deep generative neural networks [7] to produce fake image content of celebrities and politicians.”
Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward (2021, background): “character’s assassination of renowned people to defame them [14], blackmailing individuals for monetary benefits, or to create political or religious unrest by targeting politicians or religious scholars with fake videos/speeches [17], etc.”
Deep Learning for Deepfakes Creation and Detection (2019, unknown): “It is threatening to world security when deepfake methods can be employed to create videos of world leaders with fake speeches for falsification purposes [9,10].”
Limits of Deepfake Detection: A Robust Estimation Viewpoint (2019, background): “Such “democratization of fraud,” can have particularly grave consequences for politics and international affairs where it could be used to incite violence, discredit leaders and institutions, or even tip elections [6] and exacerbate disinformation wars that disrupt domestic politics [7], [8], [9].”