基于Transformer神经机器翻译的文本隐写方法

TEXT STEGANOGRAPHY METHOD BASED ON TRANSFORMER NEURAL MACHINE TRANSLATION

  • 摘要: 针对基于机器翻译的文本隐写方法存在的翻译质量差、隐藏容量低的问题,提出一种基于Transformer神经机器翻译的文本隐写方法。通过使用较为先进的神经机器翻译模型以及加入隐藏模块的Beam Search解码器,能够根据秘密信息在每一时间步输出与之对应的BPE编码,实现在翻译的过程中嵌入秘密信息。实验结果表明,该方法能够生成高质量、大隐藏容量的隐写译文。与以往的方法相比,BLEU值和隐藏容量分别提升4.84和1.63百分点。

     

    Abstract: Aimed at the problems of poor translation quality and low hiding capacity of text steganography methods based on machine translation, a text steganography method based on Transformer neural machine translation is proposed. Through the use of advanced neural machine translation model and Beam Search decoder with hidden module, the corresponding BPE code could be output according to the secret information at each time step, and the secret information could be embedded in the process of translation. Experimental results show that this method can generate steganographic translation with high quality and large hidden capacity. Compared with previous methods, BLEU value and hiding capacity are improved by 4.84 and 1.63 percentage points, respectively.

     

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