A steganographic method for digital images using side match

Chang, Chin‐Chen; Tseng, Hsien-Wen

doi:10.1016/j.patrec.2004.05.006

Cited by 202 publications

(130 citation statements)

References 6 publications

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“…Wayner [45] dedicated a complete chapter in a book to what he called "life in noise", pointing to the usefulness of data embedding in noise. It is proven to be robust with respect to compression, cropping and image processing [41,61,62]. The model-based method (MB1), described in [58], generates a stego-image based on a given distribution model, using a generalized Cauchy distribution, that results in the minimum distortion.…”

Section: Adaptive Steganographymentioning

confidence: 99%

Digital image steganography: Survey and analysis of current methods

et al. 2010

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Steganography is the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio, and video files. It comes under the assumption that if the feature is visible, the point of attack is evident, thus the goal here is always to conceal the very existence of the embedded data. Steganography has various useful applications. However, like any other science it can be used for ill intentions. It has been propelled to the forefront of current security techniques by the remarkable growth in computational power, the increase in security awareness by, e.g., individuals, groups, agencies, government and through intellectual pursuit. Steganography's ultimate objectives, which are undetectability, robustness (resistance to various image processing methods and compression) and capacity of the hidden data, are the main factors that separate it from related techniques such as watermarking and cryptography. This paper provides a state-of-the-art review and analysis of the different existing methods of steganography along with some common standards and guidelines drawn from the literature. This paper concludes with some recommendations and advocates for the object-oriented embedding mechanism. Steganalysis, which is the science of attacking steganography, is not the focus of this survey but nonetheless will be briefly discussed.

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Section: Adaptive Steganographymentioning

confidence: 99%

Digital image steganography: Survey and analysis of current methods

et al. 2010

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“…Larger PSNR values imply that the distortion between the cover image and stego−image is imperceptible to the human vision system (HVS). For evaluating the performance of our proposal three difference predictors [18], side match predic− tor [12,19], and JPEG−LS predictor [20] are used in the experiment. Figure 4 shows the position of the input pixel P(x, y) and its neighbour position in the images.…”

Section: Resultsmentioning

confidence: 99%

“…Hence, the LSB substitution scheme is not a good choice for embedding data in a smooth region. Thus, several new data hiding schemes are developed while keep− ing human eye sensitivity in mind [12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Steganographic data hiding in image processing using predictive differencing

Weng

Tso²,

Wang

2012

Opto-Electronics Review

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In this paper, we propose a stenography scheme based on predictive differencing to embed data in a grey-image. In order to promote the embedding capacity of pixel-value differencing (PVD), we use differencing between a predictive value and an input pixel as the predictive differencing to embed the message where a predictive value is calculated by using various predictors. If the predictive differencing is large, then it means that the input pixel is located in the edge area and, thus, has a larger embedding capacity than the pixel in a smooth area. The experimental result shows that our proposed scheme is capable of providing greater embedding capacity and high quality of stego-images then previous works. Furthermore, we have also applied various predictors to evaluate our proposed scheme.

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“…Chang's [3] stego image respectively. Figure 2 (d), (e) and (f) show a histogram charting the difference between consecutive pixels of the cover image, our stego image and Chang's stego image respectively.…”

Section: Extracting and Verifying Of The Secret Informationmentioning

confidence: 99%

“…for effective image steganography. Therefore most steganographic methods [1,2,3,4] focus on these requirements, and the embedding and extracting algorithm etc. In steganograpahic system, however, the receiver, who received the massage, wants to know whether the extracted message has integrity or not.…”

Section: Introductionmentioning

confidence: 99%

A novel steganographic system with information integrity

Park¹,

Kang

Yamaguchi³

et al. 2007

IEICE Electron. Express

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Abstract:We propose a novel steganographic system that is able to provide a high quality stego image in spite of the high capacity of the concealed information. The number of insertion bits in a pixel is different according to each pixel's characteristics. In addition to that, our system is able to verify whether if the secret information was sent from the sender correctly or if an attacker forged the secret message. We use two frequency coefficients in DCT domain to generate the symbol code to check the integrity of secret information.

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A steganographic method for digital images using side match

Cited by 202 publications

References 6 publications

Digital image steganography: Survey and analysis of current methods

Digital image steganography: Survey and analysis of current methods

Steganographic data hiding in image processing using predictive differencing

A novel steganographic system with information integrity

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