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Deepfake Detection in Video Samples
Krumpholc, Jan ; Veigend, Petr (oponent) ; Lapšanský, Tomáš (vedoucí práce)
In last years, we could see increase of internet frauds and forgeries. Starting with easier detectable cases like phishing and fake ads, through social engeneering and disinformation campaigns, and ending with attacks using artificial inteligence: Synthetics media, and especially deepfakes. These attacks are very effective because it's difficult to validate authenticity of deepfake media for basic user, and they are in rise in last few years with availability and effectivity of creation tools for public. This thesis is focused on video deepfakes: What methods are used for their creation, what are their weak points, and mainly, how to find these weaknesses and decide, whenever media is deepfake or not. We will analyze state-of-the-art methods of detecting deepfakes, what are their strengths and weaknesses, and develop possible new methods of detection. In the end we will compare results with modern solutions and evaluate result.
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