Extracting Spread-Spectrum Hidden Data From Digital Media

Author

Ming Li ; Kulhandjian, M.K. ; Pados, Dimitris A. ; Batalama, Stella N. ; Medley, M.J.

Author_Institution

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

Volume

8

Issue

7

fYear

2013

fDate

Jul-13

Firstpage

1201

Lastpage

1210

Abstract

We consider the problem of extracting blindly data embedded over a wide band in a spectrum (transform) domain of a digital medium (image, audio, video). We develop a novel multicarrier/signature iterative generalized least-squares (M-IGLS) core procedure to seek unknown data hidden in hosts via multicarrier spread-spectrum embedding. Neither the original host nor the embedding carriers are assumed available. Experimental studies on images show that the developed algorithm can achieve recovery probability of error close to what may be attained with known embedding carriers and host autocorrelation matrix.

Keywords

feature extraction; image watermarking; iterative methods; least squares approximations; matrix algebra; spread spectrum communication; M-IGLS core procedure; blind data embedded extraction; digital media; digital medium; error recovery probability; host autocorrelation matrix; multicarrier spread-spectrum embedding carrier; multicarrier-signature iterative generalized least-squares core algorithm; spread-spectrum hidden data extraction; Bit error rate; Correlation; Data mining; Gray-scale; Media; Transforms; Vectors; Authentication; annotation; blind detection; covert communications; data hiding; information hiding; spread-spectrum embedding; steganalysis; steganography; watermarking;

fLanguage

English

Journal_Title

Information Forensics and Security, IEEE Transactions on

Publisher

ieee

ISSN

1556-6013

Type

jour

DOI

10.1109/TIFS.2013.2264462

Filename

6517928