One Sentence, Two Meanings: Semantic Multiplexing for LLM-Generated Text Steganography

Semantic steganography typically hides information by generating LLM text via mapping secret bits to a single semantic space. A natural text, however, can readily convey two distinct meanings rooted in different domains of knowledge through a single carrier. In this work, we attempt to transform this polysemy of natural language into a measurable semantic steganographic channel resource, called semantic multiplexing. We introduce Iphis, a steganographic protocol that embeds two independent secret bit streams in one carrier. For knowledge bases such as urban traffic and computer networks, there are homographs like "traffic" and "path", called pivot words. Iphis introduces joint semantic coordinates to encode the semantics from two different spaces, and uses pivot words to assist LLM in generating carrier sentences. Text generated by Iphis has two layers of semantics: the surface semantics can be naturally understood, while the inner ones can only be extracted when corresponding knowledge base is revealed. Our evaluation indicates that the second semantic stream doubles the matched payload per carrier, initially demonstrating potential of semantic multiplexing. The evaluation also shows that a warden without key cannot recover hidden meaning.