Blind Watermark Estimation Attack for Spread Spectrum Watermarking

This paper presents an efficient scheme for blind watermark estimation embedded using additive watermark embedding methods. The scheme exploits mutual independence between the host media and the embedded watermark and non-Gaussianity of the host media for watermark estimation. The proposed scheme employs the framework of independent component analysis (ICA) and poses the problem of watermark estimation as a blind source separation (BSS) problem. Analysis of the scheme shows that the proposed detector significantly outperforms existing correlation-based blind detectors traditionally used for SS-based watermarking. The proposed ICA-based blind detection/decoding scheme has been simulated using real-world audio clips. The simulation results show that the proposed ICA-based method can detect and decode watermark with extremely low decoding bit error probability (less than 0.01) against common watermarking attacks and benchmark degradations.