Deep image steganalysis network based on coordination attention mechanism

Chen Xie

doi:10.1117/12.2679101

8 May 2023 Deep image steganalysis network based on coordination attention mechanism

Chen Xie

Proceedings Volume 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023); 126351F (2023) https://doi.org/10.1117/12.2679101
Event: International Conference on Algorithms, Microchips, and Network Applications 2023, 2023, Zhengzhou, China

Abstract

To improve the detection effect of image steganalysis on whether unknown images contain secret information, a novel deep steganalysis model based on coordination attention mechanism is proposed. Firstly, a high-pass filter groups is used to process the input image to acquire the noise residual features almost unrelated to the image content to eliminate the effect of the image content, which is conducive to the subsequent convolutional layer to model the image features. Secondly, the convolutional layer and attention mechanism are combined in the body part of the network, which can not only enhance the useful feature flow, but also boost the network to consider the discriminating features. Finally, the global average pooling layer is employed to aggregate features of channel dimension to generate the feature descriptors, and the fully connected layer is utilized to classification. The probability of input image being identified as the stego image and the cover image is acquired by the softmax operation. A lot of experiments prove that our network is better than the existing deep image steganalysis model.

Citation Download Citation

Chen Xie "Deep image steganalysis network based on coordination attention mechanism", Proc. SPIE 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023), 126351F (8 May 2023); https://doi.org/10.1117/12.2679101

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