Researchers claim biometric deepfake detection method improves state-of-the-art

Biometrics can effectively be used to detect deepfakes, according to a paper from a team of Italian and German researchers reported by Unite.AI, and could be a less "unwieldy" method of doing so than detecting synthetic artefacts and other methods. The framework for the method specifies the use of at least ten genuine videos of the subject to train the biometric model, the researchers from the University of Federico II in Naples and the Technical University of Munich write. The research into'Audio-Visual Person-of-Interest DeepFake Detection' has been posted to Arxive, and describes what the authors say is a new state-of-the-art in deepfake detection. In testing against well-known datasets, the researchers improved area under curve (AUC) scores by 3 and 10 for accuracy identifying genuine high and low-quality videos, respectively, and 7 percent for deepfake videos. Interestingly, on high-quality videos, the worst-performing system delivered deepfake detection accuracy of above 69 percent.