HiTMS: A High-Throughput Multi-Stream Linguistic Steganography Framework
Generative linguistic steganography conceals secret bits within the sampling randomness of large language models. Existing schemes are single-stream, conveying an entire secret through a single response to a single prompt. This convention incurs limitations: it provides no protocol-level support for batched multi-stream inference, and naive co-batching does not conceal slot occupancy or payload completion. We propose the High-Throughput Multi-Stream (HiTMS) framework, which distributes a secret across multiple responses produced jointly over successive rounds of interaction. Each round embeds and extracts several streams within a single batched call, thereby amortizing the cost of model i...
| Authors | Ruiyi Yan, Zhongliang Yang, Yugo Murawaki |
|---|---|
| Primary category | cs.CR |
| Published | 26 July 2026 |
| Last updated at source | 29 July 2026 |
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