5 accepted papers
Effective sequence modeling fundamentally requires balancing the retention of unbounded history with the high-resolution detection of abrupt short-term variations common in real-world phenomena. However, existing state space models (SSMs) relying on high-order polynomial projection operators (HiPPO)…
With the increasing prevalence of surveillance, safeguarding personal privacy has become a critical concern. To protect privacy, various linguistic steganography methods have been developed to conceal private information within seemingly innocuous text for covert communication. However, these method…
Steganography, which hides messages within innocent-looking carriers, is an essential technique to protect data privacy. The rapid advancement of generative models makes AI-generated images a potential steganographic carrier. However, the distortion resulting from the embedding of messages makes it…
Generative Linguistic Steganography (GLS) is applied to protect privacy against excessive censorship by employing Language Models (LMs) to hide privacy messages in texts. To effectively circumvent censorship, GLS generates steganographic texts (stegos) that closely resemble normal human texts (cover…
Linguistic steganalysis is the technology to distinguish whether looking-innocent texts hide covert (possibly hazardous) messages. Traditional methods, dominantly focusing on internal linguistic difference in texts, are seriously challenged by the recent linguistic steganography technology that can…