Steganalysis for HEVC video based on multi-scale residual convolution network

The information exchange, in the forms of pictures, voice, video and other multimedia, plays an important role in network communication, as well as many illegal information disseminations are hidden. Steganalysis is an effective way of detecting secret information. This paper proposes a universal HEVC video steganalysis algorithm based on multi-scale residual convolution network, mainly consisting of residual calculation, feature extraction and binary classification. In the feature extraction part, residual convolution layer, multi-scale residual convolution module and a steganalysis residual block are proposed. Our experimental results show that the detection rate of this method based on video pixel domain analysis network is as high as 99.75%, which has greater advantages than the traditional manual feature extraction methods. © 2021, Editorial Board of JBUAA. All right reserved.