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We introduce a new type of format-transforming encryption where the format ofciphertexts is implicitly encoded within a machine-learned generative model.Around this primitive, we build a system for covert messaging over large,public internet platforms (e.g., Twitter). Loosely, our system composes anauthenticated encryption scheme, with a method for encoding random ciphertextbits into samples from the generative model's family of seed-indexedtoken-distributions. By fixing a deployment scenario, we are forced to considersystem-level and algorithmic solutions to real challenges -- ~such asreceiver-side parsing ambiguities, and the low information-carrying capacity ofactual token-distributions~ -- that were elided in prior work. We use GPT-2 asour generative model so that our system cryptographically transforms plaintextbitstrings into natural-language covertexts suitable for posting to publicplatforms. We consider adversaries with full view of the internet platform'scontent, whose goal is to surface posts that are using our system for covertmessaging. We carry out a suite of experiments to provide heuristic evidence ofsecurity and to explore tradeoffs between operational efficiency anddetectability.

Covert Message Passing over Public Internet Platforms Using Model-Based Format-Transforming Encryption