Video Steganography by Neural Networks Using Hash Function

Submitted by grigby1 on Mon, 02/10/2020 - 11:44am

Title	Video Steganography by Neural Networks Using Hash Function
Publication Type	Conference Paper
Year of Publication	2019
Authors	Velmurugan, K.Jayasakthi, Hemavathi, S.
Conference Name	2019 Fifth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
Date Published	March 2019
Publisher	IEEE
ISBN Number	978-1-7281-1599-3
Keywords	Artificial neural networks, composability, Computer science, cryptography, data mining, digital video, discrete wavelet transforms, hash, hash algorithm, Hash Function, hybrid neural networks, Image Steganography, Metrics, MSE, neural nets, Neural networks, privacy, PSNR, pubcrawl, steganographic techniques, steganography, steganography detection, stego video, STEM, telecommunication security, video, video content, video signal processing, video steganography
Abstract	Video Steganography is an extension of image steganography where any kind of file in any extension is hidden into a digital video. The video content is dynamic in nature and this makes the detection of hidden data difficult than other steganographic techniques. The main motive of using video steganography is that the videos can store large amount of data in it. This paper focuses on security using the combination of hybrid neural networks and hash function for determining the best bits in the cover video to embed the secret data. For the embedding process, the cover video and the data to be hidden is uploaded. Then the hash algorithm and neural networks are applied to form the stego video. For the extraction process, the reverse process is applied and the secret data is obtained. All experiments are done using MatLab2016a software.
URL	https://ieeexplore.ieee.org/document/8918877
DOI	10.1109/ICONSTEM.2019.8918877
Citation Key	velmurugan_video_2019

Groups:

Science of Security VO