Deepfake detection technique based on improved transformer model

Abstract

Deepfake open source technology has lowered the threshold for AI face swapping to a very low level, making it possible to swap faces with one click. The cost of "disinformation" is greatly reduced, so that some deeply faked pictures and videos can be spread on social networks The social network can spread explosively. However, in the defense layer, there are almost no standardized and automated detection tools for deepfake. There is no such tool. Therefore, whether for individuals or platforms, the time window for fighting fake and disinformation is very short, but it is very difficult. In this paper, we use the Transformer model as a base, improve the model and optimize the structure of the model, so that the model can extract the depth features of the video and build a more accurate and efficient deepfake inspection method.