2021/04/20 by Honai Ueoka, Ueoka, Honai, Yugo Murawaki +3 · 2 citations
Computer Science · #Advanced Steganography and Watermarking Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Natural Language Processing Techniques
paper · pdf · doi:10.48550/arxiv.2104.09833
openalex publication_date 2021/04/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With advances in neural language models, the focus of linguistic\nsteganography has shifted from edit-based approaches to generation-based ones.\nWhile the latter's payload capacity is impressive, generating genuine-looking\ntexts remains challenging. In this paper, we revisit edit-based linguistic\nsteganography, with the idea that a masked language model offers an\noff-the-shelf solution. The proposed method eliminates painstaking rule\nconstruction and has a high payload capacity for an edit-based model. It is\nalso shown to be more secure against automatic detection than a\ngeneration-based method while offering better control of the security/payload\ncapacity trade-off.\n