Efficient Provably Secure Linguistic Steganography via Range Coding

Computer Science > Computation and Language [Submitted on 9 Apr 2026] Efficient Provably Secure Linguistic Steganography via Range Coding Ruiyi Yan, Yugo Murawaki Linguistic steganography involves embedding secret messages within seemingly innocuous texts to enable covert communication. Provable security, which is a long-standing goal and key motivation, has been extended to language-model-based steganography. Previous provably secure approaches have achieved perfect imperceptibility, measured by zero Kullback-Leibler (KL) divergence, but at the expense of embedding capacity. In this paper, we attempt to directly use a classic entropy coding method (range coding) to achieve secure steganography, and then propose an efficient and provably secure linguistic steganographic method with a rotation mechanism. Experiments across various language models show that our method achieves around 100% entropy utilization (embedding efficiency) for embedding capacity, outperforming the existing baseline methods. Moreover, it achieves high embedding speeds (up to 1554.66 bits/s on GPT-2). The code is available at this http URL. Comments: ACL2026 Main Subjects: Computation and Language (cs.CL); Cryptography and Security (cs.CR) Cite as: arXiv:2604.08052 [cs.CL]   (or arXiv:2604.08052v1 [cs.CL] for this version)   https://doi.org/10.48550/arXiv.2604.08052 Focus to learn more Submission history From: Ruiyi Yan [view email] [v1] Thu, 9 Apr 2026 10:00:53 UTC (912 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CL < prev   |   next > new | recent | 2026-04 Change to browse by: cs cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)