Authors
Title
Detection of JSteg Algorithm Using Hypothesis Testing Theory and a Statistical Model with Nuisance Parameters
In
Proc. of ACM Information Hiding and Multimedia Security Workshop (IH&MMSec)
Pages
3–13
Publisher
ACM
Year
2014
Publisher's URL
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Abstract
This paper investigates the statistical detection of data hid-
den within DCT coefficients of JPEG images using a Lapla-
cian distribution model. The main contributions is twofold.
First, this paper proposes to model the DCT coefficients
using a Laplacian distribution but challenges the usual as-
sumption that among a sub-band all the coefficients follow
are independent and identically distributed (i. i. d. ). In this
paper it is assumed that the distribution parameters change
from DCT coefficient to DCT coefficient. Second this pa-
per applies this model to design a statistical test, based on
hypothesis testing theory, which aims at detecting data hid-
den within DCT coefficient with the JSteg algorithm. The
proposed optimal detector carefully takes into account the
distribution parameters as nuisance parameters. Numerical
results on simulated data as well as on numerical images
database show the relevance of the proposed model and the
good performance of the ensuing test.
Affiliations
Offprint
- TQ_Jsteg_detection_IHMMSec_2014.pdf (0.6 Mo)