The impressive rise of Deep Learning and, more specifically, the discovery of generative adversarial networks has revolutionised the world of Deepfake. The forgeries are becoming more and more realistic, and consequently harder to detect. Attesting whether a video content is authentic is increasingly sensitive. Furthermore, free access to forgery technologies is dramatically increasing and very worrying. Numerous methods have been proposed to detect these deepfakes and it is difficult to know which detection methods are still accurate regarding the recent advances. Therefore, an approach for face swapping detection in videos, based on residual signal analysis is presented in this paper.