Video authentication using spatio-temporal signature for surveillance system

Kroputaponchai, Teerasak; Suvonvorn, Nikom

doi:10.1109/jcsse.2015.7219764

Cited by 4 publications

(10 citation statements)

References 6 publications

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“…Although the variables used for the hash and distances are integers, one can use a theoretical analysis on continuous data given the large number of features and video samples in our experiments. If the compared hashes in (32) correspond to two videos that are completely independent and visually distinct, the terms |H…”

Section: A Hash Analysismentioning

confidence: 99%

“…Given 200 distinct videos, 19900 identification distances have been computed using (32). The distribution of the distance is illustrated by Fig.…”

Section: A Hash Analysismentioning

confidence: 99%

“…(i) The entire DLBM features are used as a fingerprint without the hash extraction stage 5 to assess the gain of the proposed hash extraction technique (i.e., the signal calibration technique). (ii) The proposed hashing system is also assessed using the Euclidean Distance (EC) as a similarity measure to evaluate the gain offered by the proposed identification distance D id (see (32)). This is denoted by 'Proposed/EC'.…”

Section: B Identification Performancementioning

confidence: 99%

“…In the rest of the paper, s = 5 is adopted. Next, we include three video hashing techniques that have been used in authentication, namely SVD-based hashing [6], 3D DCT hashing [10], and 2D HOG hashing [32]. Similar to the previous identification experiments, the system has also been used with the Euclidean distance to illustrate the efficiency of the proposed authentication distance Decomposition (SVD) where the first eigenvalue is used to classify uniform and non-uniform blocks.…”

Section: Authentication Performancementioning

confidence: 99%

“…However, the evaluation of the system's performance on maliciously manipulated videos was not considered. More recently, Kroputaponchai and Suvonvorn [32] proposed an authentication scheme based on a twodimensional (2D) version of the Histogram of Gradient (HOG) by further considering the temporal dimension as an extension of the conventional HOG. This was, however, tested on a few videos only.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Perceptual Video Hashing for Content Identification and Authentication

Khelifi

Bouridane

2019

IEEE Trans. Circuits Syst. Video Technol.

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Abstract-Perceptual hashing has been broadly used in the literature to identify similar contents for video copy detection. It has also been adopted to detect malicious manipulations for video authentication. However, targeting both applications with a single system using the same hash would be highly desirable as this saves the storage space and reduces the computational complexity. This paper proposes a perceptual video hashing system for content identification and authentication. The objective is to design a hash extraction technique that can withstand signal processing operations on one hand and detect malicious attacks on the other hand. The proposed system relies on a new signal calibration technique for extracting the hash using the discrete cosine transform (DCT) and the discrete sine transform (DST). This consists of determining the number of samples, called the normalizing shift, that is required for shifting a digital signal so that the shifted version matches a certain pattern according to DCT/DST coefficients. The rationale for the calibration idea is that the normalizing shift resists signal processing operations while it exhibits sensitivity to local tampering (i.e., replacing a small portion of the signal with a different one). While the same hash serves both applications, two different similarity measures have been proposed for video identification and authentication, respectively. Through intensive experiments with various types of video distortions and manipulations, the proposed system has been shown to outperform related state-of-the art video hashing techniques in terms of identification and authentication with the advantageous ability to locate tampered regions.

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Section: A Hash Analysismentioning

confidence: 99%

“…Given 200 distinct videos, 19900 identification distances have been computed using (32). The distribution of the distance is illustrated by Fig.…”

Section: A Hash Analysismentioning

confidence: 99%

Section: B Identification Performancementioning

confidence: 99%

Section: Authentication Performancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Perceptual Video Hashing for Content Identification and Authentication

Khelifi

Bouridane

2019

IEEE Trans. Circuits Syst. Video Technol.

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Video Authentication Using Watermark and Digital Signature—A Study

Sowmya

Chennamma²

2016

Advances in Intelligent Systems and Computing

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Video Authentication using PLEXUS Method

Abdulwahab¹,

Hameed²,

Barnouti³

2018

ijacsa

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Digital Video authentication is very important issue in day to day life. A lot of devices have got the ability of recording or capturing digital videos and all these videos can be passed through the internet as well as many other non-secure channels. There is a problem of illegal updating or manipulation of digital video because of the development in video editing software. Therefore, video authentication techniques are required in order to ensure trustworthiness of the video. There are many techniques used to prevent this issue like Digital Signature and Watermarking, these solutions are successfully included in copyright purposes but it's still really difficult to implement in many other situations especially in video surveillance. In this paper, a new method called PLEXUS is proposed for digital video authentication on temporal attacks. In authentication process, the sender will generate a signature according to the method steps using a video and private key. In verification process, the receiver will also generate a signature using the same video and private key then each signature will be compared. If the two signatures are matched then the video is not tampered otherwise the video is tampered. This method is implemented using 10 different videos and proved to be an efficient method.

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Video authentication using spatio-temporal signature for surveillance system

Cited by 4 publications

References 6 publications

Perceptual Video Hashing for Content Identification and Authentication

Perceptual Video Hashing for Content Identification and Authentication

Video Authentication Using Watermark and Digital Signature—A Study

Video Authentication using PLEXUS Method

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