The invention discloses a false face video identification method and system based on a convolutional neural network and an attention mechanism, and a readable storage medium. The method comprises thesteps: carrying out the sampling of an inputted video sequence, and obtaining N video frames; detecting, cutting and aligning the video frame to a human face to obtain a high-quality human face image,and obtaining a to-be-detected sample set; inputting the to-be-tested sample set into a trained deep convolutional neural network model of an attention mechanism to obtain an output result which is aresult of judging the authenticity of the video. According to the method disclosed in the invention, the negative sample is obtained through the special processing method of the positive sample, thetime cost of obtaining the negative sample is reduced, the face image of the fake face video is simulated well, and the trained network has good identification capability; in addition, the method canhighlight the manipulated image regions, thereby guiding the neural network to detect the regions, facilitating the detection of face counterfeiting, and improving the accuracy of an original CNN model.