基于对抗机制的彩色图像隐写分析算法

Color Image Steganalysis Algorithm Based on Adversarial Mechanisms

针对彩色图像的隐写分析问题,引入逐通道卷积、多激活模块以及对抗机制,提出了一种应用于彩色图像隐写分析的深度卷积网络。逐通道卷积能够避免削弱不相关噪声信号,保留更多的隐写嵌入特征;多激活模块利用多种激活函数对卷积结果进行非线性映射,针对嵌入痕迹做出不同反馈,丰富嵌入特征的多样表达;对抗机制能够将内容信息特征和隐写嵌入特征从域类别上严格划分,从而分离出更多的隐写存在性特征。在PPG-LIRMM-COLOR数据集上针对多种隐写算法进行了检测实验。结果显示:所提算法比对照方法中性能最好的还要高1.83%~4.99%。实验结果验证了该彩色图像隐写分析方法的有效性。

Aiming at the steganalysis of color images,a deep convolutional network applied to the steganalysis of color images was proposed by introducing channel-wise convolution,multiple activation module and adversarial mechanism.Channel-wise convolution could avoid weakening irrelevant noise signals and retain additional steganographic embedded features;and multiple activation modules could use various activation functions to nonlinearly map convolution results and make different feedback for embedded traces to enrich the diverse expressions of embedded features;adversarial mechanisms could divide content information features and steganographic embedding features from domain categories,thereby separating additional steganographic existence features.Experiments were carried out on the PPG-LIRMM-COLOR dataset for various steganographic algorithms.The proposed algorithm was 1.83%-4.99% higher performance than the best performance in the control methods.Results verified the effectiveness of the proposed color image steganalysis method.