Uncovering the Hidden Threat of Text Watermarking from Users with Cross-Lingual Knowledge

Ghanim, Mansour Al, Xue, Jiaqi, Hastuti, Rochana Prih, Zheng, Mengxin, Solihin, Yan, Lou, Qian

arXiv.org Artificial Intelligence 

In this study, we delve into the hidden threats posed to text watermarking by users with cross-lingual knowledge. While most research focuses on watermarking methods for English, there is a significant gap in evaluating these methods in cross-lingual contexts. This oversight neglects critical adversary scenarios involving cross-lingual users, creating uncertainty regarding the effectiveness of cross-lingual watermarking. We assess four watermarking techniques across four linguistically rich languages, examining watermark resilience and text quality across various parameters and attacks. Our focus is on a realistic scenario featuring adversaries with cross-lingual expertise, evaluating the adequacy of current watermarking methods against such challenges.