A novel approach for image steganalysis

Abstract

Since JPEG images have been widely used in our daily life, the steganalysis for JPEG images becomes very important and significant. The Article addresses steganalysis in static images based on DCT transformed region, able to recognize the most popular steganography algorithms occurring on the Internet. We propose a new steganalysis method, where statistical properties of the image are explored, regardless the embedding procedure employed. The feature set used for classification of images consists of 285 statistical features. Experimental results show that in comparing with the universal steganalysis method for JPEG stego images, our method improves detection of widely used steganographic method in detection process, which provides observable differences in investigation performance.