Dynamic Content Selection Framework Applied to Coverless Information Hiding

Abstract

The traditional information hiding (IH) methods usually modify the carrier in accordance with certain rules to embed secret information. In this way, it is inevitable to leave some modification traces on the carrier, so that these methods are difficult to effectively resist the detection of various types of steganalysis algorithms. In order to fundamentally resist steganalysis, recently, a novel information hiding technique, called coverless information hiding (CIH), has been proposed to hide secret information into natural carrier without modification. In this paper, we propose a dynamic content selection framework (DCSF) for CIH to hide secret text information into natural images. To realize the CIH, the proposed framework dynamically selects images to represent the secret information via the mapping relationships constructed between the inherent features of the images and the secret information. More specifically, after constructing the mapping relationships by using a function of the values of local features, we choose multiple blocks from a natural image to represent the corresponding secret fragments. Moreover, to improve the security, we use a random label sequence to decide which blocks of the image will be chosen for the representation. In addition, since the required images may not be found in the image database, the approximate matching algorithm based on synonym and homonym is also proposed to find the images to approximately represent the secret information. Experimental results and analysis show that the proposed framework has good performance in anti-steganalysis and capacity.