Results 11  20
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54
Squin, “Some theoretical aspects of watermarking detection
 in Proc. Security, steganography and watermarking of multimedia content
, 2006
"... This paper considers watermarking detection, also known as zerobit watermarking. A watermark, carrying no hidden message, is inserted in content. The watermark detector checks for the presence of this particular weak signal in content. The paper aims at looking to this problem from a classical dete ..."
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This paper considers watermarking detection, also known as zerobit watermarking. A watermark, carrying no hidden message, is inserted in content. The watermark detector checks for the presence of this particular weak signal in content. The paper aims at looking to this problem from a classical detection theory point of view, but with side information enabled at the embedding side. This means that the watermarking signal is a function of the host content. Our study is twofold. The first issue is to design the best embedding function for a given detection function (a NeymanPearson detector structure is assumed). The second issue is to find the best detection function for a given embedding function. This yields two conditions, which are mixed into one ‘fundamental ’ differential equation. Solutions to this equation are optimal in these two senses. Interestingly, there are other solutions than the regular quantization index modulation scheme. The JANIS scheme, for instance, invented in a heuristic manner several years ago, is justified as it is one of these solutions. 1.
ML detection of steganography
 Proceedings SPIE, Electronic Imaging, Security, Steganography, and Watermarking of Multimedia Contents VII
, 2005
"... Digital steganography is the art of hiding information in multimedia content, such that it remains perceptually and statistically unchanged. The detection of such covert communication is referred to as steganalysis. To date, steganalysis research has focused primarily on either, the extraction of fe ..."
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Digital steganography is the art of hiding information in multimedia content, such that it remains perceptually and statistically unchanged. The detection of such covert communication is referred to as steganalysis. To date, steganalysis research has focused primarily on either, the extraction of features from a document that are sensitive to the embedding, or the inference of some statistical difference between marked and unmarked objects. In this work, we evaluate the statistical limits of such techniques by developing asymptotically optimal tests (Maximum Likelihood) for a number of side informed embedding schemes. The required probability density functions (pdf) are derived for Dither Modulation (DM) and DistortionCompensated Dither Modulation (DCDM/SCS) from an steganalyst’s point of view. For both embedding techniques, the pdfs are derived in the presence and absence of a secret dither key. The resulting tests are then compared to a robust blind steganalytic test based on feature extraction. The performance of the tests is evaluated using an integral measure and receiver operating characteristic (ROC) curves.
DitherModulation Data Hiding with DistortionCompensation: Exact Performance Analysis and an Improved Detector for JPEG Attacks
 in Proc. of the IEEE International Conference on Image Processing (ICIP
, 2003
"... The binary Distortion Compensated DitherModulation (DCDM) , which can be regarded to as a baseline for quantizationbased datahiding methods, is rigorously analyzed. A novel and accurate procedure for computing the exact probability of bit error is given, as well as an approximation amenable to d ..."
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Cited by 4 (2 self)
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The binary Distortion Compensated DitherModulation (DCDM) , which can be regarded to as a baseline for quantizationbased datahiding methods, is rigorously analyzed. A novel and accurate procedure for computing the exact probability of bit error is given, as well as an approximation amenable to differentiation which allows to obtain the optimal weights in a newly proposed decoding structure, for significant improvements on performance. The results are particularized for a JPEG compression scenario which allows to show their usefulness. Experimental results validating the proposed theory are presented.
Steganalysis of QIMBased Data Hiding using Kernel Density Estimation
"... This paper presents a novel steganalysis technique to attack quantization index modulation (QIM) steganography. Our method is based on the observation that QIM embedding disturbs neighborhood correlation in the transform domain. We estimate the probability density function (pdf) of this statistical ..."
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This paper presents a novel steganalysis technique to attack quantization index modulation (QIM) steganography. Our method is based on the observation that QIM embedding disturbs neighborhood correlation in the transform domain. We estimate the probability density function (pdf) of this statistical change in a systematic manner using a kernel density estimate (KDE) method. The estimated parametric density model is then used for stego message detection. The impact of the choice of kernels on the estimated density is investigated experimentally. Simulation results evaluated on a large dataset of 6000 quantized images indicate that the proposed method is reliable. The impact of the choice of message embedding parameters on the accuracy of the steganalysis detection is also evaluated. Simulation results show that the proposed method can distinguish between the quantizedcover and the QIMstego with low false alarm rates (i.e. Pfn ≤ 0.03 and Pfp ≤ 0.19). We demonstrate that the proposed steganalysis scheme can successfully attack steganographic tools like Jsteg and JP Hide and Seek as well.
Watermark security via secret wavelet packet subband structures
 Communications and Multimedia Security. Proceedings of the Seventh IFIP TC6 TC11 Conference on Communications and Multimedia Security, volume 2828 of Lecture Notes on Computer Science
, 2003
"... Abstract. Wavelet packet decompositions generalize the classical pyramidal wavelet structure. We use the vast amount of possible wavelet packet decomposition structures to create a secret wavelet domain and discuss how this idea can be used to improve the security of watermarking schemes. Two method ..."
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Abstract. Wavelet packet decompositions generalize the classical pyramidal wavelet structure. We use the vast amount of possible wavelet packet decomposition structures to create a secret wavelet domain and discuss how this idea can be used to improve the security of watermarking schemes. Two methods to create random wavelet packet trees are discussed and analyzed. The security against unauthorized detection is investigated. Using JPEG and JPEG2000 compression we assess the normalized correlation and Peak Signal to Noise Ratio (PSNR) behavior of the watermarks. We conclude that the proposed systems show improved robustness against compression and provide around 2 1046 possible keys. The security against unauthorized detection is greatly improved. 1
Optimal Strategies For SpreadSpectrum And QuantizedProjection Image Data Hiding Games with BER Payoffs
 in Proc. of the IEEE International Conference on Image Processing (ICIP
, 2003
"... We analyze spreadspectrum and quantization projection data hiding methods from a gametheoretic point of view, using the bit error rate (BER) as the payoff, and assuming that the embedder simply follows pointbypoint constraints given by a perceptual mask, whereas for the attacker an MSElike con ..."
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We analyze spreadspectrum and quantization projection data hiding methods from a gametheoretic point of view, using the bit error rate (BER) as the payoff, and assuming that the embedder simply follows pointbypoint constraints given by a perceptual mask, whereas for the attacker an MSElike constraint is imposed. The optimal attacking and decoding strategies are obtained by making use of a theorem that in addition states that those strategies constitute an equilibrium of the game. Experimental results supporting our analyses are also shown.
Asymmetric Spread Spectrum DataHiding For Laplacian Host Data
 IEEE International Conference on Image Processing ICIP 2005
, 2005
"... Spread spectrum (SS) or knownhoststatistics technique has shown the best performance in terms of both rate of reliable communications and bit error probability at the low watermarktonoise ratio (WNR) regime. These results were obtained assuming that the host data follows an independent and ide ..."
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Spread spectrum (SS) or knownhoststatistics technique has shown the best performance in terms of both rate of reliable communications and bit error probability at the low watermarktonoise 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 datahiding transform domains (like wavelet or discrete cosine transform domains) the host statistics have strong nonGaussian character. Motivated by this stochastic modeling mismatch between the used assumption and the real case, a new setup of the SSbased datahiding 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.
Steganalysis of QIM Steganography Using Irregularity Measure
"... This paper presents a nonparametric steganalysis technique to attack quantization index modulation (QIM) steganography and JSteg steganographic tool. The proposed scheme is based on the observation that message embedding using QIM introduces local irregularity (or randomness) in the coverobject. P ..."
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This paper presents a nonparametric steganalysis technique to attack quantization index modulation (QIM) steganography and JSteg steganographic tool. The proposed scheme is based on the observation that message embedding using QIM introduces local irregularity (or randomness) in the coverobject. Presented steganalysis technique exploits rich spatial/temporal correlation in the multimediaobjects to estimate local irregularity in the testobject. The underlying density function based on local irregularity in the testobject is estimated in a systematic manner using a kernel density estimate (KDE) method. The Tsallisdivergence, a parametric divergence method, is used to quantify irregularity in the testobject. The Tsallisdivergence between the density function estimated from the testobject and its doublyquantized version is used to distinguish between the cover and the stego. The impact of the choice of message embedding parameters such as quantization stepsize, quality factor, etc. on the accuracy of the steganalysis detection for gray scale images is also evaluated. Simulation results presented for these message embedding parameters show that the proposed method can successfully distinguish between the quantizedcover and the QIMstego with low false alarm rates. Detection performance of the proposed steganalysis scheme is also evaluated for JSteg steganographic tool.