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Zaharis, A, Martini, A, Tryfonas, T, Ilioudis, C and Pangalos, G (2011)

Lightweight Steganalysis Based on Image Reconstruction and Lead Digit Distribution Analysis

nternational Journal of Digital Crime and Forensics 3(4), pp. 29-41.

ISSN/ISBN: Not available at this time. DOI: 10.4018/jdcf.2011100103

Abstract: This paper presents a novel method of JPEG image Steganalysis, driven by the need for a quick and accurate identification of stego-carriers from a collection of files, where there is no knowledge of the steganography algorithm used, nor previous database of suspect carrier files created. The suspicious image is analyzed in order to identify the encoding algorithm while various meta-data is retrieved. An image file is then reconstructed in order to be used as a measure of comparison. A generalization of the basic principles of Benford’s Law distribution is applied on both the suspicious and the reconstructed image file in order to decide whether the target is a stego-carrier. The authors demonstrate the effectiveness of the technique with a steganalytic tool that can blindly detect the use of JPHide/JPseek/JPHSWin, Camouflage and Invisible Secrets. Experimental results show that the steganalysis scheme is able to efficiently detect the use of different steganography algorithms without the use of a time consuming training step, even if the embedding data rate is very low. The accuracy of the detector is independent of the payload. The method described can be generalized in order to be used for the detection of different type images which act as stego-carriers

@article{, issn = {1941-6210}, journal = {International Journal of Digital Crime and Forensics}, pages = {29--41}, volume = {3}, number = {4}, year = {2011}, title = {Lightweight Steganalysis Based on Image Reconstruction and Lead Digit Distribution Analysis}, author = {Zaharis, Alexandros and Martini, Adamantini and Tryfonas, Theo and Ilioudis, Christos and Pangalos, G}, doi = {10.4018/jdcf.2011100103}, url = {}, }

Reference Type: Journal Article

Subject Area(s): Image Processing