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dc.contributor.authorAl-Athamneh, Mohammad
dc.contributor.authorCrookes, Danny
dc.contributor.authorFarid, Mohsen
dc.date.accessioned2016-11-24T15:39:01Z
dc.date.available2016-11-24T15:39:01Z
dc.date.issued2016-12-06
dc.identifier.citationAl-Athamneh, A. et al. (2016) "Video authentication based on statistical local information", Proceedings of the 9th International Conference on Utility and Cloud Computing, Tongji University, Shanghai, China, 6-9 Decemberen
dc.identifier.isbn9781450346160.
dc.identifier.urihttp://hdl.handle.net/10545/621053
dc.description.abstractWith 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.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://computing.derby.ac.uk/ucc2016/en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectVideo authenticationen
dc.subjectTamper detectionen
dc.subjectDigital forensicsen
dc.subjectTampering attacks.en
dc.titleVideo authentication based on statistical local informationen
dc.typeMeetings and Proceedingsen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalProceedings of the 9th International Conference on Utility and Cloud Computingen
html.description.abstractWith 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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