中圖分類號(hào)： TP18
文獻(xiàn)標(biāo)識(shí)碼： A
DOI： 10.19358/j.issn.2096-5133.2021.04.005
引用格式： 李永強(qiáng),，白天. 基于卷積LSTM的視頻中Deepfake檢測(cè)方法[J].信息技術(shù)與網(wǎng)絡(luò)安全，2021,，40(4)：28-32.

Deepfake detection method in videos based on convolutional LSTM

Abstract： The face forgery technology represented by deepfake can replace the face in video with the target face by using a small amount of face data, so as to achieve the purpose of forgery video. The abuse of this kind of technology will bring adverse social effects, which need to be punished by using detection technology. The existing methods have some limitations, single frame detection algorithm ignores the dynamic defect of deepfake; when the data has defects, the model may fall into the trap of "learning specific face". In this paper, we propose a forgery face detection method in video, which uses the convolutional LSTM combined with CNN and LSTM to judge if a video is original or manipulated by deepfake. In addition, we propose a cutout method based on landmarks, which can inhibit the network from learning specific face. Experiments show that the accuracy of the baseline algorithm is improved in different scenes.

Key words : Deepfake detection；computer vision,；deep learning