Digital watermarking
Natural Language Watermarking: Design, Analysis, and a Proof-of-Concept Implementation
IHW '01 Proceedings of the 4th International Workshop on Information Hiding
Natural Language Watermarking and Tamperproofing
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
Proceedings of the 2006 ACM symposium on Applied computing
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
Words are not enough: sentence level natural language watermarking
Proceedings of the 4th ACM international workshop on Contents protection and security
Natural language watermarking via morphosyntactic alterations
Computer Speech and Language
Natural Language Watermarking for Korean Using Adverbial Displacement
MUE '08 Proceedings of the 2008 International Conference on Multimedia and Ubiquitous Engineering
Translation-based steganography
IH'05 Proceedings of the 7th international conference on Information Hiding
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We present a robust and adaptive-capacity watermarking algorithm for agglutinative languages. All processes, including the selection of sentences to be watermarked, watermark embedding, and watermark extraction, are based on syntactic dependency trees. We show that it is more robust to use syntactic dependency trees than the surface forms of sentences in text watermarking. For the agglutinative languages, we embed watermark using the two main characteristics of the languages. First, because a word consists of several morphemes, we can watermark sentences using morphological division/combination without deep linguistic analysis. Second, they permit relatively free word order, so we can move a syntactic constituent within its clause. Finally, to increase the information-hiding capacity, we adaptively compute the number of watermark bits to be embedded for each sentence. We perform three kinds of evaluation: perceptibility, robustness, and capacity of our method. High capacity is achieved by dynamically determining possibly embedded watermark bits for each sentence. The secret rank based on a syntactic dependency tree strengthens robustness of our method. Finally, we show that the displacement of syntactic constituents and morphological division/combination does not affect the style and naturalness of the text. Copyright © 2011 John Wiley & Sons, Ltd.