A High Embedding Capacity Data Hiding Scheme Based upon Permutation Vectors

Abstract

Reference-matrix-based data hiding is a way to embed secret data within cover images according to a secret reference matrix. Existing schemes such as exploiting-modification-direction-based method, Sudoku-based method, and magic-cube-based method provide several means to construct reference matrices and embed secret data by modifying the LSBs of cover images according to generated reference matrices. In order to obtain better embedding capacity and stego-image quality, we propose a novel data hiding scheme based on permutation vectors. In this proposed scheme, a 1-dimensional reference matrix is constructed by concatenating a secret permutation vector repeatedly. Experimental results show that the proposed scheme achieves higher embedding capacity and better stego-image quality. To further improve the visual quality when the embedding capacity is less than 1.5 bpp, we also propose an improved version where a 2-dimensional reference matrix is constructed based on a secret permutation vector. The experimental result also demonstrates nice visual quality of our improved scheme.