Limits of Deepfake Detection: A Robust Estimation Viewpoint

Sakshi Agarwal; Lav R. Varshney

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arXiv · 1905.03493

Limits of Deepfake Detection: A Robust Estimation Viewpoint

Sakshi Agarwal·Lav R. Varshney

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Abstract

Deepfake detection is formulated as a hypothesis testing problem to classify an image as genuine or GAN-generated. A robust statistics view of GANs is considered to bound the error probability for various GAN implementations in terms of their performance. The bounds are further simplified using a Euclidean approximation for the low error regime. Lastly, relationships between error probability and epidemic thresholds for spreading processes in networks are established.

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Sakshi Agarwal, Lav R. Varshney. 2019-05-09. Limits of Deepfake Detection: A Robust Estimation Viewpoint. https://arxiv.org/abs/1905.03493

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