Electronics, Communication & Automation Technology

A Detection Method with Deep Neural Networks for Video Motion Vector Steganography

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  • 1. School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China; 2. Sino-Singapore International Joint Research Institute,Guangzhou 510700,Guangdong,China
黄雄波(1975-),博士生,主要从事多媒体信息安全、图像处理及模式识别研究。E-mail:xb-Huang@hot-mail.com

Received date: 2019-12-19

  Revised date: 2020-03-13

  Online published: 2020-08-01

Supported by

Supported by the National Key R&D Project of China (2019QY2202) and the Science and Technology Planning Project for International Collaborative Innovation Program of Guangdong Province (2017A050501002)

Abstract

The existing deep neural network steganography detection technology was mainly proposed for digital image steganography. Since there are great differences between image steganography and video steganography,the deep neural networks designed for image steganalysis cannot be simply extended to video steganalysis. Therefore,a motion vector-modification video steganography was taken as the target example and a deep neural network for video steganalysis was proposed based on state-of-the-art image steganalysis network SRNet. A data input matrix which can well reflect the steganographic modification of motion vectors was also introduced. Experimental results demon-strate that the proposed method outperforms two traditional video steganalysis algorithms in detection accuracy for low and middle-bitrate videos,and behaves well for videos at different bitrates.

Cite this article

HUANG Xiongbo HU Yongjian WANG Yufei . A Detection Method with Deep Neural Networks for Video Motion Vector Steganography[J]. Journal of South China University of Technology(Natural Science), 2020 , 48(8) : 1 -9 . DOI: 10.12141/j.issn.1000-565X.190917

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