QUANTITATIVE STEGANALYSIS OF BINARY IMAGES (MA-L1)

Author(s) : Ming Jiang (Polytechnic University, USA) Nasir Memon (Polytechnic University, USA) Edward Wong (Polytechnic University, USA) Xiaolin Wu (McMaster University, Canada)

Abstract : We propose a quantitative steganalysis method to detect hidden information embedded by flipping pixels along boundaries in binary images. We model steganographic embedding as an additive noise process and use compression rate as a distinguishing statistic that aids in discriminating between stego-images and cover-images. We specifically use the JBIG 2 binary image compression algorithm to derive a quantitative relation between compression rate and embedding rate. Based on this relationship, a practical steganalysis technique is proposed by examining the change of compression rate as embedding rate increases. Experiments conducted show that the proposed technique can reliably detect a steganographic embedding process that flips boundary pixels. Furthermore, it can estimate embedding rate with reasonable accuracy.

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