Stegananalysis Method Based on Co-Occurrence Matrix and Neural Network
Subject Areas : electrical and computer engineeringS. Ghanbari 1 , N. Ghanbari 2 , M. Keshtgari 3 , S. H. Nabavi Karizi 4
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Keywords: Steganography steganalysis GLCM (gray level co-occurrence matrix) neural network,
Abstract :
Steganography is the art of hidden writing and secret communication. The goal of steganography is to hide the presence of information in other information. steganalysis is the art and science of detecting messages hidden using steganography. Co-occurrence matrix is the matrix containing information about the relationship between values of adjacent pixel in an image. In this paper, we extract features from Gray Level C0-occurrense Matrix (GLCM) that are difference between cover image (image without hidden information) and stego image (image with hidden information). In the proposed algorithm, first, we use a combined method of steganography based on both location and conversion to hide the information in the image. Then, using GLCM matrix properties, we investigate some difference values in the GLCM of the cover and stego images. We can extract features that were different between cover and stego images. Features are used for training neural network. This algorithm was tested on 800 standard image databases and it can detect 83% of stego images.
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