Steganalysis of JS']JSteg algorithm using hypothesis testing theory

被引:36
|
作者
Qiao, Tong [1 ]
Retraint, Florent [1 ]
Cogranne, Remi [1 ]
Zitzmann, Cathel [1 ]
机构
[1] Univ Technol Troyes, ICD, LM2S, UMR SIMR CNRS, 12 Rue Marie Curie, F-10004 Troyes, France
关键词
hypothesis testing theory; !text type='JS']JS[!/text]teg steganalysis; DCT distribution model; Hidden information detection;
D O I
10.1186/s13635-015-0019-7
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper investigates the statistical detection of JSteg steganography. The approach is based on a statistical model of discrete cosine transformation (DCT) coefficients challenging the usual assumption that among a subband all the coefficients are independent and identically distributed (i.i.d.). The hidden information-detection problem is cast in the framework of hypothesis testing theory. In an ideal context where all model parameters are perfectly known, the likelihood ratio test (LRT) is presented, and its performances are theoretically established. The statistical performance of LRT serves as an upper bound for the detection power. For a practical use where the distribution parameters are unknown, by exploring a DCT channel selection, 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.
引用
收藏
页数:16
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