Evaluating the Robustness and Accuracy of Text Watermarking Under Real-World Cross-Lingual Manipulations
This addresses a gap in evaluating watermarking for cross-lingual settings, which is important for security in multilingual applications, but it is incremental as it extends existing methods to new data.
The study benchmarks four text watermarking methods across four languages to assess their robustness and accuracy under cross-lingual manipulations, finding that current methods may not be suitable for such adversary scenarios.
We present a study to benchmark representative watermarking methods in cross-lingual settings. The current literature mainly focuses on the evaluation of watermarking methods for the English language. However, the literature for evaluating watermarking in cross-lingual settings is scarce. This results in overlooking important adversary scenarios in which a cross-lingual adversary could be in, leading to a gray area of practicality over cross-lingual watermarking. In this paper, we evaluate four watermarking methods in four different and vocabulary rich languages. Our experiments investigate the quality of text under different watermarking procedure and the detectability of watermarks with practical translation attack scenarios. Specifically, we investigate practical scenarios that an adversary with cross-lingual knowledge could take, and evaluate whether current watermarking methods are suitable for such scenarios. Finally, from our findings, we draw key insights about watermarking in cross-lingual settings.