Compression-based steganalysis of LSB embedded images

We present a new method of steganalysis, the detection of hidden messages, for least significant bits (LSB) replacement embedding. The method uses lossless image compression algorithms to model images bitplane by bitplane. The basic premise is that messages hidden by replacing LSBs of image pixels do not possess the same statistical properties and are therefore likely to be incompressible by compressors designed for images. In fact, the hidden data are usually compressed files themselves that may or may not be encrypted. In either case, the hidden messages are incompressible. In this work, we study three image compressors, one a standard and two we developed. The results are that many images can be eliminated as having possible steganographic content since the LSBs compress more than a hidden message typically would.