Abstract
Syndrome-Trellis Codes (STC), as the de facto state-of-the-art steganography framework, has drawn huge attention recently. However, the original STC merely developed with the general form of cover and message, and almost all the subsequent improvements for STC focused on the cover selection and design of the distortion cost function. How to select the optimal submatrix by the features for the given cover and message is an important issue and requires to be solved urgently. In this work, we propose to divide both the cover and message into segments and embed each message segment into its optimally matched cover segment. We name the proposed method as Segment-STC steganography. Specifically, by investigating the features of the submatrix used in STC, we first select the optimal submatrix, which could effectively reduce the number of distorted elements during the embedding. Then, the given cover and message will be split into a series of segments. Each message segment is adaptively matched with an optimal submatrix. We conduct the experiments on both the benchmark BOSS dataset and our collected on-line songs dataset. The experimental results show that, compared with the original STC, our method could effectively reduce the distortion and improve the undetectability of the stego.
Highlights
Digital steganography is the art of hiding a digital message into a digital media cover like image, audio, and video
According to the current experimental results, after segmentation, if the length of each message segment was less than 100 bits, the SegmentSTC will have a better optimization effect, and the average optimization rate can reach more than 20%
By training the CNN-based steganalysis with original Syndrome-Trellis Codes (STC), we found that the accuracy could reach up to 60%, while this phenomenon is not observed for the CNN-based steganalysis trained with the proposed Segment-STC
Summary
Digital steganography is the art of hiding a digital message into a digital media cover like image, audio, and video. A parity-check matrix is employed to embed the message into the cover with syndrome trellis codes This embedding process aims to find a stego to minimize the distortion between the original cover and the stego. MOTIVATION In the original STC framework, the authors recommended some submatrices by exhaustive search of an empirically predefined candidate set During their experiments, the used cover and message are all randomly (uniform) generated. The embedding distortion might be further reduced when we adaptively choose a submatrix for the given message and cover To better understand this situation, we provide an example as follows. We can improve the original STC steganography by finding the optimal submatrix, which can minimize the embedding distortion for the given cover and message. These four features could impact the number of possible solutions, i.e., the size of feasible set C(m) shown in (1)
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