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Computer Science
Cryptography

Video Authentication- An Overview

Profile image of Saurabh UpadhyaySaurabh Upadhyay

2011, International Journal of Computer Science & Engineering Survey

https://doi.org/10.5121/IJCSES.2011.2406
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Abstract

With the innovations and development in sophisticated video editing technology and a wide spread of video information and services in our society, it is becoming increasingly significant to assure the trustworthiness of video information. Therefore in surveillance, medical and various other fields, video contents must be protected against attempt to manipulate them. Such malicious alterations could affect the decisions based on these videos. A lot of techniques are proposed by various researchers in the literature that assure the authenticity of video information in their own way. In this paper we present a brief survey on video authentication techniques with their classification. These authentication techniques are broadly classified into four categories: digital signature based techniques, watermark based techniques, intelligent techniques and other techniques. Furthermore we give the shortcomings of different categories of video authentication techniques in brief.

FAQs

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What explains the increase in video manipulation accessibility?add

The rise of affordable and sophisticated video editing software has significantly increased access to content manipulation, complicating verification. As of 2023, tools are readily available, allowing even unskilled users to perform tampering.

How do spatio-temporal attacks differ from other tampering methods?add

Spatio-temporal attacks manipulate both spatial contents and temporal dependencies between video frames, complicating detection. The classification shows that identifying such attacks requires understanding modifications in both dimensions.

What are the components of an ideal video authentication system?add

An ideal video authentication system must support sensitivity to malicious alterations, localization of changes, and robustness against typical processing operations. According to recent studies, it should also mitigate against both false positives and negatives in detection.

When did intelligent techniques for video authentication gain prominence?add

Intelligent techniques, such as those employing Support Vector Machines, became prominent around 2015 for their database-driven classification efficiency. These techniques demonstrate high accuracy, for instance, achieving up to 99.92% classification rates in specific studies.

How effective are digital signatures compared to watermarking in video authentication?add

Digital signatures provide stronger integrity verification due to their stable characteristics against pixel modifications, outperforming fragile watermarking methods in robustness. However, if the storage location of the signature is compromised, the system becomes vulnerable.

Figures (7)
This is called the regional property of the video sequences. When a malicious alteration is performed on a video sequence, it either attacks on the contents of the video (i.e. visua information presented by the frames of the video), or attacks on the temporal dependency between the frames. A continuous video sequence V.{47, 1", f) is a scalar real valued function o Wo Spatial dimensions x and y and time t, usually observed in a rectangular spatial window W over some time interval 7. If B8{x,1,f) is modification vector then the tampered video M(x, ¥, £) would also be a scalar real valued function of spatial dimensions x and y and ime t as follows: When a video is being recorded by a video recording device, it captures the scene which is in front of the camera lens, frame by frame, with respect to time. Number of frames being captured by video recording device in a second depends on the hardware specification of the device. Thus a video sequence can be viewed as a collection of consecutive frames with temporal dependency, in a three dimensional plane, as shown in Figurel.
This is called the regional property of the video sequences. When a malicious alteration is performed on a video sequence, it either attacks on the contents of the video (i.e. visua information presented by the frames of the video), or attacks on the temporal dependency between the frames. A continuous video sequence V.{47, 1", f) is a scalar real valued function o Wo Spatial dimensions x and y and time t, usually observed in a rectangular spatial window W over some time interval 7. If B8{x,1,f) is modification vector then the tampered video M(x, ¥, £) would also be a scalar real valued function of spatial dimensions x and y and ime t as follows: When a video is being recorded by a video recording device, it captures the scene which is in front of the camera lens, frame by frame, with respect to time. Number of frames being captured by video recording device in a second depends on the hardware specification of the device. Thus a video sequence can be viewed as a collection of consecutive frames with temporal dependency, in a three dimensional plane, as shown in Figurel.
In past few years, watermarking and digital signatures have been widely used for the purpose of video authentication. Different techniques have their own advantages and shortcomings. In fact fragile watermarking and digital signatures are the two commonly used schemes for authentication.
In past few years, watermarking and digital signatures have been widely used for the purpose of video authentication. Different techniques have their own advantages and shortcomings. In fact fragile watermarking and digital signatures are the two commonly used schemes for authentication.
Figure4. A Watermarking Based Authentication System
Figure4. A Watermarking Based Authentication System
Figure5. Frames with their histogram energy for a video shot. identify the authenticity of the video. Any modification in a shot or in the important content of a shot will be reflected as changes in the computed master key. Here trajectory is constructed, using the histogram energy of the frames of the video shot. For a particular video shot, in figure 5, vertical axis indicates the histogram energy of each frame of the shot and the horizontal axis marks the frame number in the shot. A polyline belonging to the video shot is drawn which is a motion trajectory. This figure also shows the process of key frames extraction from the video shot.
Figure5. Frames with their histogram energy for a video shot. identify the authenticity of the video. Any modification in a shot or in the important content of a shot will be reflected as changes in the computed master key. Here trajectory is constructed, using the histogram energy of the frames of the video shot. For a particular video shot, in figure 5, vertical axis indicates the histogram energy of each frame of the shot and the horizontal axis marks the frame number in the shot. A polyline belonging to the video shot is drawn which is a motion trajectory. This figure also shows the process of key frames extraction from the video shot.
International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.4, November 2011 This is Lagrange interpolation formulation where the x; position refers to each key frame and J; is the pixel value of the key frames. By using this equation and extrapolation a frame at + = 0) is computed, which is regarded as the secret key. Considering the set of secret keys as another set of shares, the master key frame is computed for that particular video. With this scheme any video can be authenticated by comparing its computed master key with the original master key. This comparison can be performed by using the general cosine correlation measure given by:
International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.4, November 2011 This is Lagrange interpolation formulation where the x; position refers to each key frame and J; is the pixel value of the key frames. By using this equation and extrapolation a frame at + = 0) is computed, which is regarded as the secret key. Considering the set of secret keys as another set of shares, the master key frame is computed for that particular video. With this scheme any video can be authenticated by comparing its computed master key with the original master key. This comparison can be performed by using the general cosine correlation measure given by:

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