[Papers](https://steganography.live/reading-list/papers/) / fang-2017

Early neural approaches

# Generating Steganographic Text with LSTMs

Tina Fang, Martin Jaggi, Katerina Argyraki

First arXiv submission: May 30, 2017 · ACL 2017 Student Research Workshop

Published version: July 2017. The publication and preprint records below retain their own dates and identifiers.

Uses an LSTM language model and vocabulary bins to generate text carrying a secret bitstream. Experiments on tweets and email explore the trade-off between embedding capacity and text quality.

[Read paper ↗](https://aclanthology.org/P17-3017/) · [PDF ↗](https://aclanthology.org/P17-3017.pdf) · [Code ↗](https://github.com/tbfang/steganography-lstm)

## Relationship to Neural Linguistic Steganography

The 2019 Neural Linguistic Steganography paper cites this earlier neural method and reimplements its block-based encoding with GPT-2 as a baseline.

## Scope and limitations

The paper leaves formal evaluation against human judges and steganalysis methods to future work; its qualitative examples alone do not establish statistical undetectability.

## Cite this paper

### Published version

Tina Fang, Martin Jaggi, Katerina Argyraki. [Generating Steganographic Text with LSTMs](https://aclanthology.org/P17-3017/). Proceedings of ACL 2017, Student Research Workshop, 2017

[Published version BibTeX](https://steganography.live/reading-list/papers/fang-2017/publication.bib) · [Published version CSL-JSON](https://steganography.live/reading-list/papers/fang-2017/publication.csl.json)
Show BibTeX`@inproceedings{fang-2017-publication,
  title = {{Generating Steganographic Text with LSTMs}},
  author = {Fang, Tina and Jaggi, Martin and Argyraki, Katerina},
  year = {2017},
  booktitle = {Proceedings of ACL 2017, Student Research Workshop},
  pages = {100--106},
  publisher = {Association for Computational Linguistics},
  url = {https://aclanthology.org/P17-3017/}
}
`

### arXiv preprint

Tina Fang, Martin Jaggi, Katerina Argyraki. [Generating Steganographic Text with LSTMs](https://arxiv.org/abs/1705.10742v1). arXiv:1705.10742. First submission: May 30, 2017.

This citation records the first arXiv version and its original title. The version-specific link distinguishes it from later revisions; cite the version supporting your claim.

[arXiv preprint BibTeX](https://steganography.live/reading-list/papers/fang-2017/preprint.bib) · [arXiv preprint CSL-JSON](https://steganography.live/reading-list/papers/fang-2017/preprint.csl.json)
Show BibTeX`@misc{fang-2017-preprint,
  title = {{Generating Steganographic Text with LSTMs}},
  author = {Fang, Tina and Jaggi, Martin and Argyraki, Katerina},
  year = {2017},
  publisher = {arXiv},
  eprint = {1705.10742v1},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/1705.10742v1}
}
`

## Primary sources

- [Published author order, title, venue, July 2017, pages; no DOI listed.](https://aclanthology.org/P17-3017/)

- [First arXiv submission May 30, 2017.](https://arxiv.org/abs/1705.10742)

- [Sections 3–4 describe LSTM/bin encoding and experiments; section 5 identifies future security evaluation.](https://aclanthology.org/P17-3017.pdf)

- [Sections 2 and 4 identify Fang et al. as the Block baseline and explain the GPT-2 reimplementation.](https://aclanthology.org/D19-1115.pdf)

- [Author repository explicitly identifies itself as code for this paper.](https://github.com/tbfang/steganography-lstm)

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These notes are an editorial reading aid. Consult the primary sources for the authors’ claims, assumptions, and experiments.