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The first step towards deepfake detection is extracting all visible faces in the picture or the video.
After detecting the face(s), our deepfake detection technology gets activicated and analyzes the faces to find deepfake traces.
The output of the analysis includes the probability of the input being a deepfake and the Activation Map to substantiate the classification.
Image analysis time
Most current digital identity solutions can identify common methods of attack, such as the OBS virtual camera. However, when the attack methods get more advanced, these systems are prone to get fooled. With countless unknown attack methods out there, the chances of deepfakes being mistaken for a real person increase.
DuckDuckGoose offers a solution to this problem, as our software is built to detect the actual fake content itself rather than just how it's being presented. This means we can provide a more reliable and effective solution, even when faced with advanced or unknown attack methods.
Classifications that were actually fake
Fakes that are correctly predicted
Deepfakes are becoming more and more accessible and it is only a matter of time before they find their way into politics. The collaboration with DuckDuckGoose allows us to quickly assess a potential deepfake video and act accordingly
DuckDuckGoose and DataChecker have been a dynamic duo in the fight against deepfake attacks. The integration of DuckDuckGoose's explainable deepfake detection technology has made DataChecker's identity verification process not only more secure but also transparent and trustworthy.