Papers by Yaofei Wang
Breaking the "Provable Security": Detecting Finite-Precision Artifacts in LLM-based Steganography via Low-Probability Vanishing (2026.findings-acl)
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| Challenge: | Recent advances in Large Language Models have fostered a new class of generative linguistic steganography, claim “provably secure” by theoretically aligning the stego distribution with the language model’s natural distribution. |
| Approach: | They propose a framework that transforms the detection task from semantic classification to a statistical audit of the sampling mechanism. |
| Outcome: | The proposed framework breaks the security of AC and Meteor with high detection accuracy, whereas state-of-the-art semantic steganalyzers degrade to random guessing. |