Steganalysis Against Difference Expansion Based Reversible Data Hiding Schemes for 2D Vector Maps

The difference expansion based (DE-based) reversible data hiding schemes suit different types of vector maps respectively, and show good performance, both in capacity and invisibility. In addition, the schemes are strictly reversible. The potential applications of the data hiding schemes may include map data authentication, secret communication, and so on. However, a loophole exists in the DE-based data hiding schemes. Through analyzing the DE-based embedding behavior and the effect of embedding on the histogram of coordinate differences or Manhattan distance differences, this paper finds unusual gaps in the histogram which reveal the presence of secret data. Furthermore, by deducing and analyzing the coordinate or Manhattan distance difference histogram of a stego-map, we can get a formula of the estimated embedding rate, and estimate the length of hidden data through the use of Laplace curve fitting function. Adopted practical map datum, computing results show that this paper’s scheme is applicable to the vector maps represented by polygons or polygonal lines. Moreover, it is possible to extend this paper’s scheme to some other data sets, e.g., 3D polygonal meshes, or images.