Zero-shot Generative Linguistic Steganography

arXiv:2403.10856v1 Announce Type: new
Abstract: Generative linguistic steganography attempts to hide secret messages into covertext. Previous studies have generally focused on the statistical differences between the covertext and stegotext, however, ill-formed stegotext can readily be identified by humans. In this paper, we propose a novel zero-shot approach based on in-context learning for linguistic steganography to achieve better perceptual and statistical imperceptibility. We also design several new metrics and reproducible language evaluations to measure the imperceptibility of the stegotext. Our experimental …

abstract arxiv context cs.cl cs.cr differences generative hide however humans in-context learning messages novel paper secret statistical steganography studies type zero-shot