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Book ChapterDOI

Video Authentication Using Relative Correlation Information and SVM

01 Jan 2008-pp 511-529
About: The article was published on 2008-01-01. It has received 11 citation(s) till now. The article focuses on the topic(s): Authentication & Support vector machine.

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Topics: Authentication (55%), Support vector machine (51%)
Citations
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01 Jan 2012-
TL;DR: The issues in the designing of a video authentication system include the classification of tampering attacks, levels of tampering attack and robustness, and the categorization of existing video authentication techniques with their shortcomings are presented.

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Abstract: Video authentication aims to ensure the trustworthiness of the video by verifying the integrity and source of video data. It has gained much attention in the recent years. In this paper we present the issues in the designing of a video authentication system. These issues include the classification of tampering attacks, levels of tampering attack and robustness. Further we present the categorization of existing video authentication techniques with their shortcomings. Moreover we have also given the challenging scenarios in which the video authentication would be a critical task.

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26 citations


Cites background or methods from "Video Authentication Using Relative..."

  • ...Moreover embedding the watermark may change the content of video which is not permissible in court of law [33]....

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  • ...The proposed algorithm in [33] is validated using a database of 795 tampered and non tampered videos and the results of algorithm show a classification accuracy of 99....

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  • ...A lot of works have been done that briefly address the classification based on where [33], [5]....

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  • ...In some applications the authenticity of video data is of paramount interest such as in video surveillance, forensic investigations, law enforcement and content ownership [33]....

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  • ...This attack is intended to camouflage the actual content and provide incorrect information [33]....

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Journal ArticleDOI
TL;DR: A brief survey on video authentication techniques with their classification is presented, broadly classified into four categories: digital signature based techniques, watermarkbased techniques, intelligent techniques and other techniques.

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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.

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17 citations


Cites background or methods from "Video Authentication Using Relative..."

  • ...Moreover there also have been works on intelligent techniques for video authentication [33, 45]....

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  • ...Moreover embedding the watermark may change the content of video which is not permissible in court of law [33]....

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  • ...In today’s digital era, communication and compression techniques facilitate sharing of multimedia data such as image and video [33]....

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  • ...The proposed algorithm in [33] is validated using a database of 795 tampered and non tampered videos and the results of algorithm show a classification accuracy of 99....

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  • ...This algorithm [33] is performed in two stages: (1) SVM training and (2) Tamper detection and classification, using SVM....

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Proceedings ArticleDOI
Saurabh Upadhyay, Sanjay Singh1Institutions (1)
22 Dec 2011-
TL;DR: An intelligent video authentication algorithm using support vector machine, which is a non-linear classifier, which computes the local information of the difference frames of given video statistically and classifies the video as tampered or non-tampered.

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Abstract: With the innovations and development in sophisticated video editing technology, it is becoming increasingly significant to assure the trustworthiness of video information. Today digital videos are also increasingly transmitted over non secure channels such as Internet. Therefore in surveillance, medical and various other fields, video contents must be protected against attempt to manipulate them. This paper presents an intelligent video authentication algorithm using support vector machine, which is a non-linear classifier. The proposed algorithm does not require the computation and storage of any secret key or embedding of any watermark. It computes the local information of the difference frames of given video statistically and classifies the video as tampered or non-tampered. It covers both kinds of tampering attacks, spatial and temporal. It uses a database of more than 4000 tampered and non-tampered video frames and gives excellent results with 99.12 classification accuracy.

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12 citations


Proceedings ArticleDOI
Ankita Gupta1, Shilpi Gupta1, Anu Mehra1Institutions (1)
01 Feb 2015-
TL;DR: An algorithm that is divided in two parts: computing the repeated frames by processing the image pixels to produce a frame-by-frame motion energy time and computing the tampering attack and its location with the help of the Support Vector Machine helps to predict whether the given video has been tampered or not.

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Abstract: The large amount of video content is being transmitted over internet and other channels. With the help of existing multimedia editing tools one can easily change the content of data which lead to lose the authenticity of the information. Thus, it becomes necessary to develop different methods by which the authenticity of the videos can be confirmed. In the past researchers have proposed several methods for authentication of videos. This paper presents an algorithm that is divided in two parts: computing the repeated frames by processing the image pixels to produce a frame-by-frame motion energy time and computing the tampering attack and its location with the help of the Support Vector Machine. This helps to predict whether the given video has been tampered or not.

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9 citations


Cites background from "Video Authentication Using Relative..."

  • ...Therefore it has become important for the scientific communities to come up methods regarding the authenticating video recordings [8,12]....

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  • ...have been done in to the matter regarding the information including every pixels as well as frames [12]....

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Proceedings ArticleDOI
06 Dec 2016-
TL;DR: 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.

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Abstract: 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.

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5 citations


Cites background from "Video Authentication Using Relative..."

  • ...Keywords Video authentication; Tamper Detection; Digital Forensics; Tampering Attacks....

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  • ...Frame addition: where one or more frames are inserted within the sequence of frames....

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References
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Book
Vladimir Vapnik1Institutions (1)
01 Jan 1995-
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?

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Abstract: Setting of the learning problem consistency of learning processes bounds on the rate of convergence of learning processes controlling the generalization ability of learning processes constructing learning algorithms what is important in learning theory?.

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38,164 citations


Journal ArticleDOI
Whitfield Diffie1, Martin E. Hellman1Institutions (1)
TL;DR: This paper suggests ways to solve currently open problems in cryptography, and discusses how the theories of communication and computation are beginning to provide the tools to solve cryptographic problems of long standing.

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Abstract: Two kinds of contemporary developments in cryptography are examined. Widening applications of teleprocessing have given rise to a need for new types of cryptographic systems, which minimize the need for secure key distribution channels and supply the equivalent of a written signature. This paper suggests ways to solve these currently open problems. It also discusses how the theories of communication and computation are beginning to provide the tools to solve cryptographic problems of long standing.

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14,068 citations


01 Jan 1995-
TL;DR: Videre: Journal of Computer Vision Research is a quarterly journal published electronically on the Internet by The MIT Press, Cambridge, Massachusetts, 02142 and prices subject to change without notice.

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Abstract: Videre: Journal of Computer Vision Research (ISSN 1089-2788) is a quarterly journal published electronically on the Internet by The MIT Press, Cambridge, Massachusetts, 02142. Subscriptions and address changes should be addressed to MIT Press Journals, Five Cambridge Center, Cambridge, MA 02142; phone: (617) 253-2889; fax: (617) 577-1545; e-mail: journals-orders@mit.edu. Subscription rates are: Individuals $30.00, Institutions $125.00. Canadians add additional 7% GST. Prices subject to change without notice.

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1,133 citations


Journal ArticleDOI
TL;DR: A new digital signature scheme which makes use of an image's contents (in the wavelet transform domain) to construct a structural digital signature (SDS) for image authentication, which can tolerate content-preserving modifications while detecting content-changing modifications.

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Abstract: The existing digital data verification methods are able to detect regions that have been tampered with, but are too fragile to resist incidental manipulations. This paper proposes a new digital signature scheme which makes use of an image's contents (in the wavelet transform domain) to construct a structural digital signature (SDS) for image authentication. The characteristic of the SDS is that it can tolerate content-preserving modifications while detecting content-changing modifications. Many incidental manipulations, which were detected as malicious modifications in the previous digital signature verification or fragile watermarking schemes, can be bypassed in the proposed scheme. Performance analysis is conducted and experimental results show that the new scheme is indeed superb for image authentication.

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375 citations


7


Proceedings ArticleDOI
04 Oct 1998-
TL;DR: A scheme for authenticating the visual content of digital images is proposed, robust to compression noise, but will detect deliberate manipulation of the image-data.

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Abstract: It is straightforward to apply general schemes for authenticating digital data to the problem of authenticating digital images. However, such a scheme would not authenticate images that have undergone lossy compression, even though they may not have been manipulated otherwise. We propose a scheme for authenticating the visual content of digital images. This scheme is robust to compression noise, but will detect deliberate manipulation of the image-data. The proposed scheme is based on the extraction of feature-points from the image. These feature-points are defined so as to be relatively unaffected by lossy compression. The set of feature-points from a given image is encrypted using public key encryption, to generate the digital signature of the image. Authenticity is verified by comparing the feature-points of the image in question, with those recovered from the previously computed digital signature.

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230 citations


Network Information
Performance
Metrics
No. of citations received by the Paper in previous years
YearCitations
20191
20171
20161
20154
20121
20113