Chaos based Edge Adaptive Image Steganography

Roy, Ratnakirti; Sarkar, Anirban; Changder, Suvamoy

doi:10.1016/j.protcy.2013.12.346

Cited by 56 publications

(20 citation statements)

References 15 publications

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“…These techniques employ a high payload but are vulnerable to image processing manipulations and statistical attacks such as image cropping, image compressing, noise attacks and chi-square attack. Some examples of spatial domain techniques include LSB [8][9][10][11], gray-level modification method [12], edges based embedding techniques [4,[13][14][15][16], pixel indicator techniques (PIT) [17,18], pixel value differencing techniques [19,20], pixel pair matching method [21], and tri-way pixel value differencing method [22]. In transform domain, the image is converted from the spatial domain to the transform domain and the image coefficients are modified to hide secret information.…”

mentioning

confidence: 99%

A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

Muhammad

Sajjad

Mehmood

et al. 2015

Multimed Tools Appl

139

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Image Steganography is a thriving research area of information security where secret data is embedded in images to hide its existence while getting the minimum possible statistical detectability. This paper proposes a novel magic least significant bit substitution method (M-LSB-SM) for RGB images. The proposed method is based on the achromatic component (Iplane) of the hue-saturation-intensity (HSI) color model and multi-level encryption (MLE) in the spatial domain. The input image is transposed and converted into an HSI color space. The Iplane is divided into four sub-images of equal size, rotating each sub-image with a different angle using a secret key. The secret information is divided into four blocks, which are then encrypted using an MLE algorithm (MLEA). Each sub-block of the message is embedded into one of the rotated sub-images based on a specific pattern using magic LSB substitution. Experimental results validate that the proposed method not only enhances the visual quality of stego images but also provides good imperceptibility and multiple security levels as compared to several existing prominent methods.Steganographic methods are broadly classified into spatial domain and transform domain methods. In the spatial domain, the gray levels of the original carrier image are directly modified for encoding the secret data. These techniques employ a high payload but are vulnerable to image processing manipulations and statistical attacks such as image cropping, image compressing, noise attacks and chi-square attack. Some examples of spatial domain techniques include LSB [8][9][10][11], gray-level modification method [12], edges based embedding techniques [4,[13][14][15][16], pixel indicator techniques (PIT) [17,18], pixel value differencing techniques [19,20], pixel pair matching method [21], and tri-way pixel value differencing method [22]. In transform domain, the image is converted from the spatial domain to the transform domain and the image coefficients are modified to hide secret information. These techniques have a lower payload but they are more robust against statistical attacks. Some examples of transform domain techniques are the discrete wavelength transform technique [23], discrete Fourier transform technique [24], discrete cosine transform techniques [25,26], and contourlet transform technique [27].The simplest and most basic spatial domain steganographic method is LSB substitution, which hides secret data inside a cover image. With this method, the least significant bits of the carrier image pixels are replaced with the secret data bits. Payload capacity of the LSB method can be increased if more than 1 LSBs are used for message embedding, but it makes noticeable changes in the carrier image. Wang et.al, [28] presented a genetic algorithm based on an LSB substitution scheme for improving the stego image quality. The Wang et.al, approach requires more processing time, which is its major shortcoming. To reduce the complexity of the Wang et.al, scheme, Chang et.al,[29] proposed a fast algorithm...

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mentioning

confidence: 99%

A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

Muhammad

Sajjad

Mehmood

et al. 2015

Multimed Tools Appl

139

View full text Add to dashboard Cite

show abstract

“…This paper proposes an edge adaptive image steganography mechanism which combines the benefits of matrix encoding and LSBM to embed data and also uses a chaotic mapping scheme to provide enhanced security to the payload. Efforts have been given to ensure that the proposed mechanism conforms to high Imperceptibility and Fidelity which are the essential quality requirements for any image steganography system [12].…”

Section: Related Workmentioning

confidence: 99%

An Analysis on LSB Image Steganography with Colour Image as Cover

Chaturvedi¹,

Mohi²

2018

IJCA

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LSB-based steganographic methods embed secret messages into the cover image by directly manipulating the leastsignificant-bit (LSB) plane. Although it is not the best steganographic method, LSB replacement is worth studying because of its large embedding capacity and simplicity. In LSB replacement, the LSB plane is simply replaced with the secret message so that the LSB values carry the hidden message directly. As more and more techniques of hiding information (Steganography) are developed, the methods of detecting the use of steganography (Steganalysis), also advance. Most steganography techniques change the properties of the cover source which increases the probability of detecting the changes. The DCT-M3 algorithm reduces significantly the number of changes in the cover image; the embedding capacity has been improved by 16.7% approximately while maintaining minimum detectability against blind steganalysis schemes. The effectiveness of steganography is measured using three parameters. First, the steganographic technique must provide the maximum information. Second, the embedded data must not be traceable to the viewer. Third, the hidden information should be successfully retrieved at the receiver. It is difficult to recognize the existence of a hidden data in the cover image using the existing methods. This is because embedding is randomly performed in the frequency domain. General TermsSteganography, LSB (Least Significant Bit) image.

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“…There are certain regions in an image known as regions of interest (ROI) [12]. The data embedded into these regions corresponds to lesser distortion that is better quality.…”

Section: Related Workmentioning

confidence: 99%

“…Firstly it is encrypted with the help of Arnold cat map [5,12]. In Arnold cat map the secret information iterated number of times.…”

Section: Modified Reversible Data Hiding Schemementioning

confidence: 99%

Reversible data hiding technique based on prediction error expansion and complexity gene

Kaur

Budhiraja

Dhindsa

2015

2015 2nd International Conference on Recent Advances in Engineering &Amp; Computational Sciences (RAECS)

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Data hiding is the process of concealing the existence of one type of information into another. In reversible data hiding techniques, original host image can be successfully restored from the marked image after the exact extraction of the secret information. In recent years, various modifications of this technique have been proposed. In this paper, the reversible data hiding technique based on prediction error expansion is modified by hiding the secret information using selective embedment as per complexity gene. Information hiding starts from the most complex block to lowest one which is evaluated on the basis of complexity gene. It also uses the Arnold cat map to encrypt the secret information, thus provide one more level of security to the scheme. Simulation results shows that the modified method has better PSNR, more information hiding capacity & enhanced levels of security then the existing technique.

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Chaos based Edge Adaptive Image Steganography

Cited by 56 publications

References 15 publications

A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

An Analysis on LSB Image Steganography with Colour Image as Cover

Reversible data hiding technique based on prediction error expansion and complexity gene

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