Video authentication based on statistical local information

With the outgrowth of video editing tools, video information trustworthiness becomes a hypersensitive field. Today many devices have the capability of capturing digital videos such as CCTV, digital cameras and mobile phones and these videos may transmitted over the Internet or any other non secure channel. As digital video can be used to as supporting evidence, it has to be protected against manipulation or tampering. As most video authentication techniques are based on watermarking and digital signatures, these techniques are effectively used in copyright purposes but difficult to implement in other cases such as video surveillance or in videos captured by consumer’s cameras. In this paper we propose an intelligent technique for video authentication which uses the video local information which makes it useful for real world applications. The proposed algorithm relies on the video’s statistical local information which was applied on a dataset of videos captured by a range of consumer video cameras. The results show that the proposed algorithm has potential to be a reliable intelligent technique in digital video authentication without the need to use for SVM classifier which makes it faster and less computationally expensive in comparing with other intelligent techniques.

With the outgrowth of video editing tools, video information
trustworthiness becomes a hypersensitive field. Today many
devices have the capability of capturing digital videos such as
CCTV, digital cameras and mobile phones and these videos
may transmitted over the Internet or any other non secure
channel. As digital video can be used to as supporting
evidence, it has to be protected against manipulation or
tampering.
As most video authentication techniques are based on
watermarking and digital signatures, these techniques are
effectively used in copyright purposes but difficult to
implement in other cases such as video surveillance or in
videos captured by consumer’s cameras.
In this paper we propose an intelligent technique for video
authentication which uses the video local information which
makes it useful for real world applications.
The proposed algorithm relies on the video’s statistical local
information which was applied on a dataset of videos captured
by a range of consumer video cameras.
The results show that the proposed algorithm has potential to
be a reliable intelligent technique in digital video
authentication without the need to use for SVM classifier
which makes it faster and less computationally expensive in
comparing with other intelligent techniques.