A New Genetic Algorithm Approach for Secure JPEG Steganography

Fard, Amin Milani; Mohammad-R.,; Akbarzadeh-T,; Varasteh-A., F.

doi:10.1109/iceis.2006.1703168

Cited by 47 publications

(37 citation statements)

References 3 publications

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“…Fard et al [41] state clearly that "there is currently no steganography system which can resist all steganalysis attacks". "Ultimately, image understanding is important for secure adaptive steganography.…”

Section: Originalmentioning

confidence: 99%

“…JPEG compression uses the DCT to transform successive sub-image blocks (8x8 pixels) into 64 DCT coefficients. Data is inserted into these coefficients' insignificant bits; however, altering any single coefficient would affect the entire 64 block pixels [41]. As the change is operating on the frequency domain instead of the spatial domain there will be no visible change in the cover image given those coefficients are handled with care [42].…”

Section: Steganography In the Image Frequency Domainmentioning

confidence: 99%

“…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%

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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: Originalmentioning

confidence: 99%

Section: Steganography In the Image Frequency Domainmentioning

confidence: 99%

Section: Adaptive Steganographymentioning

confidence: 99%

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Digital image steganography: Survey and analysis of current methods

et al. 2010

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“…This function called Mean Absolute Difference (MAD) is applied by Pik-Wah as an image quality indicator for his GA-based watermark algorithm [13]. Milani Fard, A. et al [14] also combined the Outguess method and MAD, as the genetic algorithm fitness function for improving the quality of their obtained stego-image.…”

Section: The Proposed Methodsmentioning

confidence: 99%

Secure Genetic Based Image Steganography System in Frequency Domain

Moghaddasi¹,

Bt²,

Manaf³

2012

IJCEE

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Abstract-Steganography is a hiding system that conceals the information in a way only the sender and the recipient know about its existence. Various steganography methods developed to cover different objectives of steganography applications. All these objectives support the main goal of steganography that is undetectability. In this paper a DCT based steganography system is proposed to embed information in 4 th bits of DCT coefficients and optimize quality of the obtained stego-images applying genetic algorithm that looks for the best position for embedding. The main idea is derived from SSB-4 method which embeds the message in more significant bits to be more resistant against various steganalysis methods. The experimental results show that the proposed method enhances the imperceptibility and undetectability of the stego-images and is resistant against some steganalysis techniques such as chi-square attack.Index Terms-Discrete cosine transform, genetic algorithm, steganography, stego-image.

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“…Most recent researches utilize Discrete Wavelet Transform (DWT because of its wide application in the new image compression standard, JPEG2000. An example is the employment of an adaptive data embedding technique with the use of OPAP to hide data in Integer Wavelet coefficients of the cover image [9].…”

Section: B Data Hiding Techniquesmentioning

confidence: 99%

Steganography Based on Integer Wavelet Transform and Bicubic Interpolation

Ajeeshvali¹,

Rajasekhar²

2012

IJIGSP

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Abstract-Steganography is the art and science of hiding information in unremarkable cover media so as not to observe any suspicion. It is an application under information security field, being classified under information security, Steganography will be characterized by having set of measures that rely on strengths and counter attacks that are caused by weaknesses and vulnerabilities. The aim of this paper is to propose a modified high capacity image steganography technique that depends on integer wavelet transform with acceptable levels of imperceptibility and distortion in the cover image as a medium file and high levels of security. Bicubic interpolation causes overshoot, which increases acutance (apparent sharpness). The Bicubic algorithm is frequently used for scaling images and video for display. The algorithm preserves fine details of the image better than the common bilinear algorithm.

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A New Genetic Algorithm Approach for Secure JPEG Steganography

Cited by 47 publications

References 3 publications

Digital image steganography: Survey and analysis of current methods

Digital image steganography: Survey and analysis of current methods

Secure Genetic Based Image Steganography System in Frequency Domain

Steganography Based on Integer Wavelet Transform and Bicubic Interpolation

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