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In this paper a joint watermarking and ciphering scheme for digital images is presented. Both operations are performed on a key-dependent transform domain. The commutative property of the proposed method allows to cipher a watermarked image without interfering with the embedded signal or to watermark an encrypted image still allowing a perfect deciphering. Furthermore, the key dependence of the transform domain increases the security of the overall system. Experimental results show the effectiveness of the proposed scheme.

A novel method for watermarking and ciphering color images, based on the joint use of a key-dependent wavelet transform with a secure cryptographic scheme, is presented. The system allows to watermark encrypted data without requiring the knowledge of the original data and also to cipher watermarked data without damaging the embedded signal. Since different areas of the proposed transform domain are used for encryption and watermarking, the extraction of the hidden information can be performed without deciphering the cover data and it is also possible to decipher watermarked data without removing the watermark. Experimental results show the effectiveness of the proposed scheme.

In this paper a novel method for watermarking and ciphering color images is presented. The aim of the system is to allow the watermarking of encrypted data without requiring the knowledge of the original data. By using this method, it is also possible to cipher watermarked data without damaging the embedded signal. Furthermore, the extraction of the hidden information can be performed without deciphering the cover data and it is also possible to decipher watermarked data without removing the watermark. The transform domain adopted in this work is the Fibonacci-Haar wavelet transform. The experimental results show the effectiveness of the proposed scheme. © 2008 SPIE-IS&T

In this paper a novel, fast, and robust data hiding technique based on key-dependent basis functions is presented. The particular domain chosen for the embedding is built on the Tree-Structured Haar basis. A weight function, based on Human Visual System features, is used as a mask for selecting the coefficients to be marked. Experimental results show the effectiveness of the proposed method.