JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2018, Vol. 53 ›› Issue (3): 63-70.doi: 10.6040/j.issn.1671-9352.2.2017.294

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Steganalysis method based on shallow convolution neural network

LIU Ming-ming, ZHANG Min-qing, LIU Jia, GAO Pei-xian   

  1. Key Laboratory of Network and Information Security Armed Police Force, Engineering University of the Armed Police Force, Xian 710086, Shaanxi, China
  • Received:2017-08-28 Online:2018-03-20 Published:2018-03-13

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Abstract: In order to improve the detection rate of steganalysis, a method of image steganalysis based on shallow convolution neural network is proposed. Compared with the deep convolution neural network, the shallow convolution neural network can improve the convergence speed of the neural network and reduce the loss of the steganography feature by reducing the convolution layer and disabling the pool layer. At the same time, the generalization performance of the steganalysis network is improved by using batch normalization functions and using a single fully connected layer. The experimental results show that the detection accuracy can reach 96% and 81.7% respectively when the embedding rate is 0.4 bpp and 0.1 bpp. And the method is still maintain a better detection performance in the case of carrier source and embedding rate mismatch.

Key words: steganalysis, shallow convolution, neural network, deep learning

CLC Number: 

  • TP309
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