@inproceedings{
ji2024a,
title={A Principled Approach to Natural Language Watermarking},
author={Zhe Ji and Qiansiqi Hu and Yicheng Zheng and Liyao Xiang and Xinbing Wang},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=mlhG8gkLnd}
}
Recently, there is a surge in machine-generated natural language content being misused by unauthorized parties. Watermarking is a well-recognized technique to address the issue by tracing the provenance of the text. However, we found most existing watermarking systems for texts are subject to ad hoc design and thus suffer from fundamental vulnerabilities. 

We propose a principled design for text watermarking based on a theoretical information-hiding framework. The watermarking party and attacker play a rate-distortion-constrained capacity game to achieve the maximum rate of reliable transmission, i.e., watermark capacity. The capacity can be expressed by the mutual information between the encoding and the attacker's corrupted text, indicating how many watermark bits are effectively conveyed under distortion constraints. The system is realized by a learning-based framework with mutual information neural estimators. In the framework, we adopt the assumption of an omniscient attacker and let the watermarking party pit against the attacker who is fully aware of the watermarking strategy. The watermarking party thus achieves higher robustness against removal attacks. We further show that the incorporation of side information substantially enhances the efficacy and robustness of the watermarking system. Experimental results have shown the superiority of our watermarking system compared to the state-of-the-art in terms of capacity, robustness, and preserving text semantics.
A Principled Approach to Natural Language Watermarking
Zhe Ji Qiansiqi Hu Yicheng Zheng Liyao Xiang Xinbing Wang