We consider the interplay between steganographer and the steganalyzer, and develop a steganalysis aware framework
for steganography. The problem of determining a stego image is posed as a feasibility problem subject to constraint of data communication, imperceptibility, and statistical indistinguishability with respect to steganalyzer's features. A stego image is then determined using set theoretic feasible point estimation methods. The proposed framework is applied effectively on a state of the art steganalysis method based on higher order statistics (HOS) steganalysis. We first show that the steganographer can significantly reduce the classification performance of the steganalyzer by employing a statistical constraint during embedding, although the image is highly distorted. Then we show that steganalyzer can develop a counter-strategy against steganographer's action, gaining back some classification performance. This interchange represents an empirical iteration in this game between the steganographer and steganalyzer. Finally we consider mixture strategies to find the Nash equilibrium of the interplay.
Spread spectrum (SS) modulation is utilized in many watermarking applications because it offers exceptional
robustness against several attacks. The embedding rate-distortion performance of SS embedding however, is
relatively weak compared to quantization index modulation (QIM). This limits the relative embedding rate of
SS watermarks. In this paper, we illustrate that both the embedding effciency, i.e. bits embedded per unit
distortion and robustness against additive white gaussian noise (AWGN) can be improved by pre-coding of
message followed by constellation adjustment on the SS detector to minimize the distortion on the cover image
introduced by coded data. Our pre-coding method encodes <i>p</i> bits as a <i>2p</i> x 1 binary vector with a single nonzero
entry whose index indicates the value of the embedded bits. Our analysis show that the method improves
embedding rate by approximately <i>p/4</i> without increasing embedding distortion or sacrificing robustness to AWGN
attacks. Experimental evaluation of the method using a set theoretic embedding framework for the watermark
insertion validates our analysis.
We present a new paradigm for the insertion of multiple watermarks in images. Instead of an explicitly defined embedding process, the watermark embedding is achieved implicitly by determining a feasible image meeting multiple desired constraints. The constraints are designed to ensure that the watermarked image is visually indistinguishable from the original and produces a positive detection result when subjected to detectors for the individual watermarks even in the presence of signal processing operations, particularly compression. We develop useful mathematical definitions of constraint sets for different visual models, for transform domain compression, and for both spread-spectrum and quantization index modulation (QIM) watermark detection scenarios. Using the constraints with a generalized vector space projections method (VSPM), we determine a watermarked signal. Experimental results demonstrate the flexibility and usefulness of the presented methodology in addressing multiple watermarking scenarios while providing implicit shaping of the watermark power to meet visual requirements.