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Video Steganography using Convolutional Neural Network and Temporal Residual Method

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Authors:
Fariha Aiman, G. R. Manjula
10.5120/ijca2019919375

Fariha Aiman and G R Manjula. Video Steganography using Convolutional Neural Network and Temporal Residual Method. International Journal of Computer Applications 178(46):24-29, September 2019. BibTeX

@article{10.5120/ijca2019919375,
	author = {Fariha Aiman and G. R. Manjula},
	title = {Video Steganography using Convolutional Neural Network and Temporal Residual Method},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2019},
	volume = {178},
	number = {46},
	month = {Sep},
	year = {2019},
	issn = {0975-8887},
	pages = {24-29},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume178/number46/30860-2019919375},
	doi = {10.5120/ijca2019919375},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Steganography involves data hiding in computer files. Steganographic coding, include a file including the document, image, program as well as guidelines, can be included in electronic communication in a transport layer. Because of their large size media files are suitable for the steganography transmission. This paper focuses on video steganography. Video steganography is nothing but hiding the complete secret video within the cover video. Firstly the residual of the secret video and cover video is obtained because hiding the residual video is much easier when compared to hiding original video. This model uses the deep convolutional neural network method. The model compares the particular model with other method. And all results show that this method is efficient.

References

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Keywords

Video steganography, Data hiding, deep neural network, residual modeling