Steganography Based on Adaptive Pixel-Value Differencing Scheme Revisited

摘要

The adaptive pixel-value differencing (APVD) based steganography proposed by Luo et al. is a state-of-the-art steganographic approach in spatial domain. It can resist blind steganalysis but is vulnerable to the targeted attack proposed by Tan et al. In this paper, we introduce an improved version of APVD. Like APVD, we also first divide an image into some non-overlapping squares and then rotate each of them by a random degree of 0, 90, 180 or 270. For an embedding unit constructed with three consecutive pixels of the resulting image, we randomly select one pixel of it for data embedding. Furthermore, the local statistical features are well preserved by exploiting neighborhood information of pixels. The experimental results evaluated on a large image database reveal that our method makes a significant improvement against the APVD-specific steganalytic attack, and has an impressive performance on resisting blind steganalysis compared with previous PVD-based steganographic methods.