Local Linear Transform and New Features of Histogram Characteristic Functions for Steganalysis of Least Significant Bit Matching Steganography
Ergong Zheng, Xijian Ping, Tao Zhang · KSII Transactions on Internet and Information Systems · 2011
In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images.Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding.Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands.A suboptimal feature set is searched by using a threshold selection algorithm.Extensive experiments are performed on four diverse uncompressed image databases.In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.