2022 IJCNLP IJCNLP 2022

Addressing Segmentation Ambiguity in Neural Linguistic Steganography

Abstract

AbstractPrevious studies on neural linguistic steganography, except Ueoka et al. (2021), overlook the fact that the sender must detokenize cover texts to avoid arousing the eavesdropper’s suspicion. In this paper, we demonstrate that segmentation ambiguity indeed causes occasional decoding failures at the receiver’s side. With the near-ubiquity of subwords, this problem now affects any language. We propose simple tricks to overcome this problem, which are even applicable to languages without explicit word boundaries.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — cover text
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio