José-Emilio Vila-Forcén

Worst-case additive attack against quantization-based data-hiding methods

The main goal of this study consists in the development of the worst case additive attack (WCAA) for quantization-based methods using as design criteria the bit error rate probability and the maximum achievable rate of reliable communications. Our analysis is focused on the practical scheme known as a distortion compensation dither modulation (DC-DM). From the mathematical point of view, the problem of the worst case attack (WCA) design using probability of error as a cost function can be formulated as the maximization of the average probability of error subject to the introduced distortion for a given decoding rule. When mutual information is selected as a cost function, a solution of the minimization problem should provide such an attacking noise probability density function (PDF) that will maximally decrease the rate of reliable communications for an arbitrary decoder structure. The results show that within the class of additive noise attacks the developed attack leads to a stronger performance decrease for the considered class of embedding techniques than the AWGN or the uniform noise attacks.

Worst case additive attack against quantization-based watermarking techniques

In the scope of quantization-based watermarking techniques and additive attacks, there exists a common belief that the worst case attack (WCA) is given by additive white Gaussian noise (AWGN). Nevertheless, it has not been proved that the AWGN is indeed the WCA within the class of additive attacks against quantization-based watermarking. In this paper, the analysis of the WCA is theoretically developed with probability of error as a cost function. The adopted approach includes the possibility of masking the attack by a target probability density function (PDF) in order to trick smart decoding. The developed attack upper bounds the probability of error for quantization-based embedding schemes within the class of additive attacks.

Quantization-based methods: additive attacks performance analysis

The main goal of this study consists in the development of the (WCAA) for ∣M∣-ary quantization-based data-hiding methods using as design criteria the error probability and the maximum achievable rate of reliable communications. Our analysis focuses on the practical scheme known as (DC-DM). From the mathematical point of view, the problem of the (WCA) design using probability of error as a cost function is formulated as the maximization of the average probability of error subject to the introduced distortion for a given decoding rule. When mutual information is selected as a cost function, a solution of the minimization problem should provide such an attacking noise probability density function that will maximally decrease the rate of reliable communications for an arbitrary decoder structure. The obtained results demonstrate that, within the class of additive attacks, the developed attack leads to a stronger performance decrease for the considered class of embedding techniques than the additive white Gaussian or uniform noise attacks.

Facial image compression based on structured codebooks in overcomplete domain

We advocate facial image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: image compression is considered from the position of source coding with side information and, contrarily to the existing scenarios where the side information is given explicitly; the side information is created based on a deterministic approximation of the local image features. We consider an image in the overcomplete transform domain as a realization of a random source with a structured codebook of symbols where each symbol represents a particular edge shape. Due to the partial availability of the side information at both encoder and decoder, we treat our problem as a modification of the Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available at the decoder. Finally, the paper presents a practical image compression algorithm for facial images based on our concept that demonstrates the superior performance in the very-low-bit-rate regime.

On reversibility of random binning techniques: multimedia perspectives

In this paper, we analyze a possibility of reversibility of data-hiding techniques based on random binning from multimedia perspectives. We demonstrate the capabilities of unauthorized users to perform hidden data removal using solely a signal processing approach based on optimal estimation as well as consider reversibility on the side of authorized users who have the knowledge of key used for the message hiding.

Robustness improvement of known-host-state data-hiding using host statistics

In this paper we considered the problem of performance improvement of known-host-state (quantization-based) watermarking methods undergo additive white Gaussian noise (AWGN) and uniform noise attacks. We question the optimality of uniform high rate quantizer based design of dither modulation and distortion compensate dither modulation methods from their robustness to these attacks point of view in terms of bit error rate probability. Motivated by superior performance of uniform deadzone quantizer over the uniform one in lossy source coding, we propose to replace the latter one by a former one designed according to the statistics of the host data. Based on suggested modifications we obtained analytical expressions for bit error rate probability analysis of quantization-based watermarking methods in AWGN and uniform noise channels. Experimental results of computer simulations demonstrated performance enhancement of known-host-state watermarking techniques in comparison to the classically elaborated schemes at negative watermark-to-noise ratios.

Practical data-hiding: additive attacks performance analysis

The main goal of this tutorial is to review the theory and design the worst case additive attack (WCAA) for

Asymmetric spread spectrum data-hiding for Laplacian host data

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Costa Problem Under Channel Ambiguity

-ary quantization-based data-hiding methods using as performance criteria the error probability and the maximum achievable rate of reliable communications. Our analysis focuses on the practical scheme known as distortion compensation dither modulation (DC-DM). From the mathematical point of view, the problem of the worst case attack (WCA) design using probability of error as a cost function is formulated as the maximization of the average probability of error subject to the introduced distortion for a given decoding rule. When mutual information is selected as a cost function, a solution to the minimization problem should provide such an attacking noise probability density function (pdf) that will maximally decrease the rate of reliable communications for an arbitrary decoder structure. The obtained results demonstrate that, within the class of additive attacks, the developed attack leads to a stronger performance decrease for the considered class of embedding techniques than the additive white Gaussian or uniform noise attacks.

Performance analysis of nonuniform quantization-based data-hiding

Spread spectrum (SS) or known-host-statistics technique has shown the best performance in terms of both rate of reliable communications and bit error probability at the low watermark-to-noise ratio (WNR) regime. These results were obtained assuming that the host data follows an independent and identically distributed (i.i.d.) Gaussian distribution. However, in some widely used in practical data-hiding transform domains (like wavelet or discrete cosine transform domains) the host statistics have strong non-Gaussian character. Motivated by this stochastic modeling mismatch between the used assumption and the real case, a new set-up of the SS-based data-hiding with Laplacian host is presented for performance enhancement in terms of both bit error probability and achievable rates in additive white Gaussian noise (AWGN) channels based on the parallel splitting of Laplacian source.