Passive spread-spectrum steganalysis

Author

Li, Ming ; Kulhandjian, Michel ; Pados, Dimitris A. ; Batalama, Stella N. ; Medley, Michael J.

Author_Institution

Dept. of Electr. Eng., State Univ. of New York at Buffalo, Buffalo, NY, USA

fYear

2011

fDate

11-14 Sept. 2011

Firstpage

1957

Lastpage

1960

Abstract

We consider the problem of passive spread-spectrum steganalysis where the objective is to decide the presence or absence of spread-spectrum hidden data in a given image (a binary hypothesis testing problem). Unlike conventional feature-based approaches, we describe an unsupervised (blind) low-complexity approach based on generalized least-squares principles that may enable rapid high-volume image processing. Extensive experiments on image sets and comparisons with existing steganalysis techniques demonstrate most satisfactory classification performance measured in probability of correct detection versus induced false alarm rate.

Keywords

image coding; least squares approximations; steganography; binary hypothesis testing problem; generalized least squares principle; image coding; image processing; passive spread spectrum steganalysis; spread spectrum hidden data; unsupervised low complexity approach; Conferences; Correlation; Data mining; Feature extraction; Vectors; Watermarking; Blind detection; covert communications; data hiding; spread-spectrum embedding; steganalysis; steganography; watermarking;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2011 18th IEEE International Conference on

Conference_Location

Brussels

ISSN

1522-4880

Print_ISBN

978-1-4577-1304-0

Electronic_ISBN

1522-4880

Type

conf

DOI

10.1109/ICIP.2011.6115856

Filename

6115856