Abstract:
Information hiding in video streams with the
development of network and multimedia technologies
has played an important role in the steganographical
field, and correspondingly video stegnanlysis techniques
are catching attention of the security d epartment of each
government. This paper presents an improved
steganalysis technique to detect the presence of hidden
me ssages. In order to identify and classify the two types
of feature are used. The first type feature is texture
feature that is computed by statistical, p sychological
and signal processing The second type feature is the
state of the art histogram based features This system is
classified by using a Support Vector Machine ( SVM
Classification is performed between actual video
frames, steganograpyh frames from MSU u nique tool
for hiding information in video) allows hiding text file in
a video sequence. SVM is excellent classifier for two
class problem that give higher detection accuracy rate
for this system. Experimental results show that the
proposed scheme can effectively detect whether a video
has been processed by stego or not.
