Title :
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
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;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6115856
