Universal secret payload location identification in spatial LSB stego images

Abstract

Locating steganographic payload is an important aspect of active steganalysis which deals with finding the pixel locations of the embedded secret message (payload) in the stego image. The residual-based payload location detectors are well suited for this purpose. In this paper, an improved universal, blind method of precisely identifying locations in the spatial domain using enhanced weighted residuals with only a few known stego images is proposed. This is done by estimating the cover from the available stego image using the proposed novel locally weighted bivariate shrinkage function in the transform domain. The enhanced weighted residuals ensure that the proposed method is universally applicable for detecting payload locations in spatial least significant bit stego images. The added advantage of the proposed method is that it does not require any prior knowledge of the cover source or the embedding algorithm to determine the exact locations. Experiments conducted on five spatial LSB domain algorithms show that the payload locations can be precisely estimated with a minimum accuracy of 90% with 100 known stego images.