Optimal detection of outguess using an accurate model of DCT coefficients

Author

Thai, Thanh Hai ; COGRANNE, Remi ; Retraint, Florent

Author_Institution

ICD - ROSAS - LM2S, Troyes Univ. of Technol., Troyes, France

fYear

2014

Firstpage

179

Lastpage

184

Abstract

This paper presents an optimal statistical test for the detection of OutGuess steganographic algorithm using an accurate statistical model of Discrete Cosine Transform (DCT) coefficients. First, this paper presents the proposed novel statistical model of quantized DCT coefficients. Then, this model is applied to design an optimal statistical test for the detection of OutGuess data hiding scheme. To this end, the detection of hidden data is cast within the framework of hypothesis testing theory. The optimal Likelihood Ratio Test (LRT) is first presented. Then, for a practical application, a Generalized LRT is proposed using Maximum Likelihood Estimations of unknown parameters. Large scale numerical results show that the proposed approach allows the reliable and efficient detection of OutGuess.

Keywords

data compression; discrete cosine transforms; image coding; maximum likelihood estimation; quantisation (signal); statistical testing; steganography; JPEG compression standard; OutGuess data hiding scheme detection; discrete cosine transform coefficients; generalized LRT; hypothesis testing theory; maximum likelihood estimations; optimal OutGuess steganographic algorithm detection; optimal likelihood ratio test; optimal statistical test design; quantized DCT coefficients; unknown parameters; Discrete cosine transforms; Estimation; Laplace equations; Mathematical model; Numerical models; Payloads; Transform coding; DCT modelling; Discrete Cosine Transform; Hypothesis Testing; OutGuess; Steganalysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Forensics and Security (WIFS), 2014 IEEE International Workshop on

Type

conf

DOI

10.1109/WIFS.2014.7084324

Filename

7084324