Steganalysis on Images using SVM with Selected Hybrid Features of Gini Index Feature Selection Algorithm

Abstract

Image steganography techniques can be classified into two major categories such as spatial domain techniques and frequency domain techniques. In spatial domain techniques the secret message is hidden inside the image by applying some manipulation over the different pixels of the image. This work attempts to detect the stego images created by WOW algorithm by steganalysis on images, based on the classification of selected Hybrid image feature sets. It uses Gini Index as the feature selection algorithm on the combined features of the Chen, SPAM and Ccpev. The main scope of this work is to compete the previously implemented SVM-spam and SVM-HT methods. It uses the standard classification performance metrics to evaluate the performance of the three of the steganalysis models SVM-spam, SVM-HT and SVM-HG (SVM with Hybrid features of Gini Index).