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Pseudorandom Error-Correcting Codes

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arxiv 2402.09370 v2 pith:C3WCQOHG submitted 2024-02-14 cs.CR cs.AIcs.LG

classification cs.CRcs.AIcs.LG
keywords codespseudorandomschemeconstanterror-correctingerrorsratesteganography
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

We construct pseudorandom error-correcting codes (or simply pseudorandom codes), which are error-correcting codes with the property that any polynomial number of codewords are pseudorandom to any computationally-bounded adversary. Efficient decoding of corrupted codewords is possible with the help of a decoding key. We build pseudorandom codes that are robust to substitution and deletion errors, where pseudorandomness rests on standard cryptographic assumptions. Specifically, pseudorandomness is based on either $2^{O(\sqrt{n})}$-hardness of LPN, or polynomial hardness of LPN and the planted XOR problem at low density. As our primary application of pseudorandom codes, we present an undetectable watermarking scheme for outputs of language models that is robust to cropping and a constant rate of random substitutions and deletions. The watermark is undetectable in the sense that any number of samples of watermarked text are computationally indistinguishable from text output by the original model. This is the first undetectable watermarking scheme that can tolerate a constant rate of errors. Our second application is to steganography, where a secret message is hidden in innocent-looking content. We present a constant-rate stateless steganography scheme with robustness to a constant rate of substitutions. Ours is the first stateless steganography scheme with provable steganographic security and any robustness to errors.

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On Computational Hardness of Mistake-Bounded Language Generation: A Random-Oracle Query Separation

    cs.CC 2026-08 accept novelty 7.0 of 10

    Under a random oracle, a countable family of infinite languages has closure dimension zero and admits zero-mistake unbounded generation, yet every polynomial-query generator incurs an exponential expected-mistake lowe...

  2. Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models

    cs.LG 2025-06 conditional novelty 7.0 of 10

    Green/red-list token watermarking survives fine-tuning in autoregressive image models, while latent-diffusion watermarks do not survive the autoencoder or the training noise process.

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