On the Extraction of Spread-Spectrum Hidden Data in Digital Media
This paper considers the problem of blindly extracting data embedded over a wide band in a spectrum (transform) domain of a digital medium (image, audio, video). The authors first develop a Multi-signature Iterative Generalized Least-Squares (MIGLS) core procedure to seek unknown data hidden in hosts via multi-signature direct-sequence spread-spectrum embedding. Neither the original host nor the embedding signatures are assumed available. Then, Cross-Correlation enhanced M-IGLS (CCM- IGLS), a procedure described herein in detail that is based on statistical analysis of repeated independent M-IGLS processing of the host, is seen to offer most effective hidden message recovery.