Steganalysis in resized images

It is well known that the security of a given steganographic algorithm strongly depends on the statistical properties of the cover source. In this paper, we study how downsampling affects steganographic security. The secure payload no longer scales according to the square-root law because resizing changes the statistical properties of the cover source. We demonstrate this experimentally for various types of resizing algorithms and their settings and thoroughly interpret the results. Modeling digital images as Markov chains allows us to compute the Fisher information rate for the simplest resizing algorithm with the box kernel and derive the proper scaling of the secure payload with resizing. The theory fits experimental data, which indicates the existence of a new scaling law expressing the length of secure payload when the cover length is not modified by adding or removing pixels but, instead, by subsampling. Since both steganography and steganalysis is today commonly evaluated through controlled experiments on resized images (e.g., the BOSSbase), the effect of resizing on security is of utmost importance to practitioners.