  A new algorithm for the detection of deepfakes in digital videos is
presented. The I-frames were extracted in order to provide faster computation
and analysis than approaches described in the literature. To identify the
discriminating regions within individual video frames, the entire frame,
background, face, eyes, nose, mouth, and face frame were analyzed separately.
From the Discrete Cosine Transform (DCT), the Beta components were extracted
from the AC coefficients and used as input to standard classifiers.
Experimental results show that the eye and mouth regions are those most
discriminative and able to determine the nature of the video under analysis.
