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This paper gives an overview of the research and implementation challenges we encountered in building an end-to-end natural language processing based watermarking system. With natural language watermarking, we mean embedding the watermark into a text document, using the natural language components as the carrier, in such a way that the modifications are imperceptible to the readers and the embedded information is robust against possible attacks. Of particular interest is using the structure of the sentences in natural language text in order to insert the watermark. We evaluated the quality of the watermarked text using an objective evaluation metric, the BLEU score. BLEU scoring is commonly used in the statistical machine translation community. Our current system prototype achieves 0.45 BLEU score on a scale 0,1.
Topkara et al. (Thu,) studied this question.