Statistical Detection of Jsteg Steganography Using Hypothesis Testing Theory
Proc. of IEEE International Conference on Image Processing (ICIP)
This paper investigates the statistical detection of Jsteg steganography. The approach is based on the statistical model of Discrete Cosine Transformation (DCT) coefficients. The hidden information detection problem is case in the frame- work of Hypothesis testing theory. In an ideal context where all model parameters are perfectly known, the Likelihood Ratio Test (LRT) is presented and its performance are the- oretically established. The statistical performance of LRT serve as an upper bound of the detection power. For a prac- tical use, when the distribution parameters are unknown, a detector based on estimation of those parameters is designed. The loss of power of the proposed detector, compared with the optimal LRT is small, which shows the relevance of the proposed approach.
- TQ_ICIP14_JSteg_Steganalysis_vc.pdf (0.5 Mo)