Hermite polynomials as provably good functions to watermark white gaussian hosts
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
A lightweight rao-cauchy detector for additive watermarking in the dwt-domain
Proceedings of the 10th ACM workshop on Multimedia and security
On the Complexity of Obtaining Optimal Watermarking Schemes
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
EURASIP Journal on Information Security
Experimental assessment of the reliability for watermarking and fingerprinting schemes
EURASIP Journal on Information Security
Estimating the probability of false alarm for a zero-bit watermarking technique
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Asymptotically optimum universal watermark embedding and detection in the high-SNR regime
IEEE Transactions on Information Theory
Sequential Monte Carlo for rare event estimation
Statistics and Computing
| Hi-index | 754.90 |
An information-theoretic approach is proposed to watermark embedding and detection under limited detector resources. First, the attack-free scenario is considered under which asymptotically optimal decision regions in the Neyman-Pearson sense are proposed, along with the optimal embedding rule. Later, the case of zero-mean independent and identically distributed (i.i.d.) Gaussian covertext distribution is explored with unknown variance under the attack-free scenario. For this case, a lower bound on the exponential decay rate of the false-negative probability is proposed. It is proven that the optimal embedding and detecting strategy is superior to the customary linear, additive embedding strategy in the exponential sense. Finally, these results are extended to the case of memoryless attacks and general worst case attacks. Optimal decision regions and embedding rules are offered, and the worst attack channel is identified.