Towards Near-imperceptible Steganographic Text
This addresses the challenge of creating less detectable hidden messages in text for security applications, but appears incremental as it builds on prior methods.
The paper tackled the problem of imperceptibility in linguistic steganography by analyzing assumptions in existing systems and proposed a patient-Huffman encoding algorithm with improved near-imperceptible guarantees.
We show that the imperceptibility of several existing linguistic steganographic systems (Fang et al., 2017; Yang et al., 2018) relies on implicit assumptions on statistical behaviors of fluent text. We formally analyze them and empirically evaluate these assumptions. Furthermore, based on these observations, we propose an encoding algorithm called patient-Huffman with improved near-imperceptible guarantees.