Steganalysis by Subtractive Pixel Adjacency Matrix

Tomas Pevny (1) , Patrick Bas (2) , Jessica Fridrich (3)

1 CTU - Czech Technical University in Prague
2 LAGIS-SI
3 Binghamton University [SUNY]

This paper presents a method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is LSB matching. First, arguments are provided for modeling the differences between adjacent pixels using first-order and second-order Markov chains. Subsets of sample transition probability matrices are then used as features for a steganalyzer implemented by support vector machines. The major part of experiments, performed on four diverse image databases, focuses on evaluation of detection of LSB matching. The comparison to prior art reveals that the presented feature set offers superior accuracy in detecting LSB matching. Even though the feature set was developed specifically for spatial domain steganalysis, by constructing steganalyzers for ten algorithms for JPEG images it is demonstrated that the features detect steganography in the transform domain as well.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Tomas Pevny, Patrick Bas, Jessica Fridrich. Steganalysis by Subtractive Pixel Adjacency Matrix. IEEE Transactions on Information Forensics and Security, 2010, 5 (2), pp.215--224. ⟨hal-00541410⟩