Abstract:
Video Steganography deals with hiding
secret data or information within a video file
without changing the video display or audio. The
secret information is embedded in the cover
frames by splitting data. If LSB (Least Significant
Bit) matching, also known as ±1 embedding, is
used, the detection rates are considerably
reduced. In particular, since LSB embedding is
modeled as an additive noise process, detection is
especially poor for images that exhibit highfrequency
noise - the high-frequency noise is often
incorrectly thought to be indicative of a hidden
message. To overcome this, we propose a targeted
steganalysis algorithm that exploits the fact that
after LSB matching, the local maxima of a video
frame gray-level or color histogram decrease and
the local minima increase. Consequently, the sum
of the absolute differences between local extrema
and their neighbors in the intensity histogram of
stego video frames will be smaller than for cover
video frames. In this paper, we use the mp4
files(less than 1 minute) which have inserted the
stego message using the LSB matching. And then,
this video is split into frames and each frame is
analysed if the stego exists or not.
