THE COMPARISON OF CLASSIFIERS IN IMAGE STEGANALYSIS
Martin Broda, Vladimír Hajduk, Dušan Levický · Acta Electrotechnica et Informatica · 2014
In this paper, proposed steganalytic method utilized for the detection of secret message is based on extraction of statistical features from cover and stego images in JPEG file format together with calibration technique.The steganalyzer concept uses Support Vector Machines (SVM) classification or Bayes classifier for training a model that is later used by the same steganalyzer in order to identify between a clean (cover) and stego image.The aim of the paper was to compare detection accuracy (ACR) of the trained models for two types of classifiers: Support Vector Machines and Bayes classifier.In this paper, five models created between cover and stego images (images obtained by nsF5, Model Based 1, Model Based 2, Modulo Histogram Fitting with Dead Zone and Pertubed Quantization steganographic method) was tested.