Fusion of Steganalysis Systems Using Bayesian Model Averaging

The increasing use of steganography requires digital forensic examiners to consider the extraction of hidden information from digital images encountered during investigations. The first step in extraction is to identify the embedding method. Several steganalysis systems have been developed for this purpose, but each system only identifies a subset of the available embedding methods and with varying degrees of accuracy. This paper applies Bayesian model averaging to fuse multiple steganalysis systems and identify the embedding used to create a stego JPEG image. Experimental results indicate that the steganalysis fusion system has an accuracy of 90% compared with 80% accuracy for the individual steganalysis systems.