Hide Chopin In The Music: Efficient Information Steganography Via Random Shuffling

Information steganography is a family of techniques that hide secret messages into a carrier; thus, the messages can only be extracted by receivers with a correct key. Although many approaches have been proposed to achieve this purpose, historically, it is a difficult problem to conceal a large amount of information without occasioning human perceptible changes. In this paper, we explore the room introduced by the low-rank property of natural signals (i.e., images, audios) and propose a training-free model for efficient information steganography, which provides a capacity of hiding full-size images into carriers of the same spatial resolution. The key of our method is to randomly shuffle the secrets and carry out a simple reduction summation with the carrier. On the other hand, the secret images can be reconstructed by solving a convex optimization problem similar to the ordinary tensor decomposition. In the experimental analysis, we carry out two tasks: concealing a full-RGB-color image into a gray-scale image; concealing images into music signals. The results confirm the ability of our model to handle massive secret payloads. The code of our paper is provided in https://github.com/minogame/ICASSP-SIC.