[R] STEGASURAS: STEGanography via Arithmetic coding and Strong neURAl modelS
We recently released our demo for our EMNLP paper “Neural Linguistic Steganography”, hiding secret messages in natural language via arithmetic coding and GPT-2. Arithmetic coding is a powerful entropy coding technique that is optimal for random sequences. Using arithmetic coding in reverse enables extremely efficient steganography, and when combined with modern language models like GPT-2 it allows for convincing cover text generations that encode information.
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