Multiclass Detector of Current Steganographic Methods for JPEG Format

Abstract

Abstract-The aim of this paper is to construct a practical forensic steganalysis tool for JPEG images that can properly analyze both single-and double-compressed stego images and classify them to selected current steganographic methods. Although some of the individual modules of the steganalyzer were previously published by the authors, they were never tested as a complete system. The fusion of the modules brings its own challenges and problems whose analysis and solution is one of the goals of this paper.By determining the stego algorithm, this tool provides the first step needed for extracting the secret message. Given a JPEG image, the detector assigns it to 6 popular steganographic algorithms. The detection is based on feature extraction and supervised training of two banks of multi-classifiers realized using support vector machines. For accurate classification of single-compressed images, a separate multi-classifier is trained for each JPEG quality factor from a certain range. Another bank of multiclassifiers is trained for double-compressed images for the same range of primary quality factors. The image under investigation is first analyzed using a pre-classifier that detects selected cases of double-compression and estimates the primary quantization table. It then sends the image to the appropriate single-or double-compression multiclassifier. The error is estimated from more than 2.6 million images. The steganalyzer is also tested on two previously unseen methods to examine its ability to generalize.

Moving steganography and steganalysis from the laboratory into the real world

“…But for law enforcement it is probably necessary to demonstrate the content of a message by extracting it, in which case the first step is to determine the embedding algorithm. This problem, largely neglected, has been studied in [81] for JPEG images. The detection of different algorithms based on statistical properties will not be perfect, as methods with similar distortion functions and embedding changes are likely to be confused, but this has not been studied for recent adaptive embedding methods.…”

Steganalysis of JSteg algorithm using hypothesis testing theory

“…It should be noted that other approaches have been proposed for the detection of data hidden within DCT coefficients of JPEG images, to cite a few, the structural detection [23], the category attack [24], the WS detector [15] and the universal or blind detectors [25,26]. However, establishing the statistical properties of those detectors remains a difficult work which has not been studied yet.…”

A Modified LSB Matching Steganography Technique for Images to Hide Executable Files

“…Then, the variance value d2 ij among the three adjacent pixels Pi 1, j, Pi, j 1 and Pi 1, j 1. can be computed by Eq. (8), and the base bi, j of P00 i; j can be derived by Eq. (9).…”

“…Meanwhile, the development of steganalytic tools are also started growing. Steganalysis is a process of finding the existence of a secret data in a cover media [8]. Whenever a suspicious image is received, the main task of a steganalytic tool is to find the algorithm used for hiding secret data in the image.…”