Developments of video processing technology make it much easier to tamper with video. In some situation, such as in a
lawsuit, it is necessary to prove videos are not tampered. This contradiction poses challenges to ascertain integrity of
digital videos. Most of tamperings occur in pixel domain. However, nowadays videos are usually stored in compressed
format, such as H.264/AVC. For attackers it is necessary to decompress original video bitstreams and recompress it into
compressed domain. As a result, by detecting double compression, we can authenticate integrity of digital video. In this
paper, we propose an efficient method to detect whether or not a digital video has been double compressed. Specifically,
we use probability distribution of quantized nonzero AC coefficients as features to distinguish double compressed video
from those original one compressed video. If a smaller QP is used in the second compression, the original distribution
law will be violated, which can be used as the evidence of tampering.
MP3 is the most popular audio format nowadays in our daily life, for example music downloaded from the Internet and
file saved in the digital recorder are often in MP3 format. However, low bitrate MP3s are often transcoded to high bitrate
since high bitrate ones are of high commercial value. Also audio recording in digital recorder can be doctored easily by
pervasive audio editing software. This paper presents two methods for the detection of double MP3 compression. The
methods are essential for finding out fake-quality MP3 and audio forensics. The proposed methods use support vector
machine classifiers with feature vectors formed by the distributions of the first digits of the quantized MDCT (modified
discrete cosine transform) coefficients. Extensive experiments demonstrate the effectiveness of the proposed methods.
To the best of our knowledge, this piece of work is the first one to detect double compression of audio signal.