Statistical Restoration for Robust and Secure Steganography

K. Solanki, K. Sullivan, U. Madhow, B. S. Manjunath, and S. Chandrasekaran
Dept. of Electrical and Computer Engineering
University of California at Santa Barbara
Santa Barbara, CA 93106


We investigate data hiding techniques that attempt to defeat steganalysis by restoring the statistics of the composite image to resemble that of the cover. The approach is to reserve a number of host symbols for statistical restoration: host statistics perturbed by data embedding are restored by suitably modifying the symbols from the reserved set. While statistical restoration has broad applicability to a variety of hiding methods, we illustrate our ideas here for quantization index modulation (QIM) based hiding. We propose a method for significantly reducing the detectability of QIM, while preserving its robustness to attacks. We next use the framework of statistical restoration to develop a method to combat steganalysis techniques which detect block-DCT embedding by evaluating the increase in blockiness of the image due to hiding. Numerical results demonstrating the efficacy of these techniques are provided.
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K. Solanki, K. Sullivan, U. Madhow, B. S. Manjunath and S. Chandrasekaran,
IEEE International Conference on Image Processing, Genova, Italy, Sep. 2005.
Node ID: 416 , DB ID: 218 , VRLID: 149 , Lab: VRL , Target: Proceedings
Subject: [Digital Watermarking and Data Hiding] « Look up more