Research on reversible image steganography of encrypted image based on image interpolation and difference histogram shift

Ye, Hanmin; Su, Keqin; Cheng, Xiaohui; Huang, Shiming

doi:10.1049/ipr2.12461

Cited by 11 publications

(5 citation statements)

References 17 publications

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“…In this study, the author used double scrambles operation on the pixel of the image by changing the positions of the pixels. The experimental results achieved a high embedding capacity and security 31 .…”

Section: Summary Of the Related Workmentioning

confidence: 92%

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

Rahman,

Uddin,

Hussain

et al. 2023

Sci Rep

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In the recent couple of years, due to the accelerated popularity of the internet, various organizations such as government offices, military, private companies, etc. use different transferring methods for exchanging their information. The Internet has various benefits and some demerits, but the primary bad mark is security of information transmission over an unreliable network, and widely uses of images. So, Steganography is the state of the art of implanting a message in the cover objects, that nobody can suspect or identify it. Therefore, in the field of cover steganography, it is very critical to track down a mechanism for concealing data by utilizing different blends of compression strategies. Amplifying the payload limit, and robustness, and working on the visual quality are the vital factors of this research to make a reliable mechanism. Different cover steganography research strategies have been recommended, and each adores its benefits and impediments but there is a need to foster some better cover steganography implements to accomplish dependability between the essential model of cover steganography. To handle these issues, in this paper we proposed a method in view of Huffman code, Least Significant Bits (LSB) based cover steganography utilizing Multi-Level Encryption (MLE) and colorless part (HC-LSBIS-MLE-AC) of the picture. It also used different substitution and flicking concepts, MLE, Magic matrix, and achromatic concepts for proving the proficiency, and significance of the method. The algorithm was also statistically investigated based on some Statistical Assessment Metrics (SAM) such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Normalized Cross Correlation (NCC), Structural Similarity Index Metric (SSIM), etc. and different perspectives. The observational outcomes show the likelihood of the proposed algorithm and the capacity to give unwavering quality between security, payload, perception, computation, and temper protection.

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Section: Summary Of the Related Workmentioning

confidence: 92%

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

Rahman,

Uddin,

Hussain

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Based on a new interpolation image and difference histogram shift, Ye et al. [21] proposed a reversible image steganography algorithm for encrypted images. To raise the embedding capacity and quality of stego images, Samar Kamil Khudhair et al.…”

Section: Related Workmentioning

confidence: 99%

“…Yu et al [20] proposed a novel reversible data hiding in encrypted domain scheme for coding channel based on sliding-block segmentation and adaptive steganography. Based on a new interpolation image and difference histogram shift, Ye et al [21] proposed a reversible image steganography algorithm for encrypted images. To raise the embedding capacity and quality of stego images, Samar Kamil Khudhair et al [22] propose a dynamic blockbased, histogram shifting-based RDH technique.…”

Section: Information Hidingmentioning

confidence: 99%

SIHNet: A safe image hiding method with less information leaking

Cheng,

Jin,

Jiang

et al. 2024

IET Image Processing

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Image hiding is a task that hides secret images into cover images. The purposes of image hiding are to ensure the secret images are invisible to the human and the secret images can be recovered. The current state‐of‐the‐art steganography methods run the risk of secret information leakage. A safe image hiding network (SIHNet) is presented to reduce the leakage of secret information. Based on some phenomena of image hiding methods which use invertible neural network, a reversible secret image processing (SIP) module is proposed to make the secret images suitable for hiding and make the stego images leak less secret information. Besides, a reversible lost information hiding (LIH) module is used to hide the lost information into the cover images, thus the method can recover the secret images better than the method that uses random noise to replace the lost information. Experimental results show that SIHNet outperforms other state‐of‐the‐art methods on the PSNR and SSIM values of the recovered secret images and the stego images. Besides, residual images of other state‐of‐the‐art methods all contain information about secret images while residual images of SIHNet leak almost no secret information. Thus the method can prevent the listener of transmission channel from obtaining the information of the secret image through the residual image, which means SIHNet performs better in security than other state‐of‐the‐art methods.

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“…Steganography is an important technology for secret information that can be disseminated across open networks [3]. The purpose of image steganography is to incorporate secret data while preventing its existence in personal communication [4]. The stego image is created by embedding the secret data in the carrier image, and one of the main goals of image steganography is to reduce the difference between the stego and carrier images [5].…”

Section: Introductionmentioning

confidence: 99%

An image steganography using improved hyper-chaotic Henon map and fractal Tromino

Nagarajegowda,

Krishnan

2023

IJECE

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<span lang="EN-US">Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. First, the cover image is converted into a wavelet environment using the integer wavelet transform (IWT), which protects the cover images from false mistakes. The grey wolf optimizer (GWO) is used to choose the pixel’s image that would be utilized to insert the hidden image in the cover image. GWO effectively selects pixels by calculating entropy, pixel intensity, and fitness function using the cover images. Moreover, the secret image was encrypted by utilizing a proposed hyper-chaotic improved Henon map and fractal Tromino. The suggested method increases computational security and efficiency with increased embedding capacity. Following the embedding algorithm of the secret image and the alteration of the cover image, the least significant bit (LSB) is utilized to locate the tempered region and to provide self-recovery characteristics in the digital image. According to the findings, the proposed technique provides a more secure transmission network with lower complexity in terms of peak signal-to-noise ratio (PSNR), normalized cross correlation (NCC), structural similarity index (SSIM), entropy and mean square error (MSE). As compared to the current approaches, the proposed method performed better in terms of PSNR 70.58% Db and SSIM 0.999 respectively.</span>

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Research on reversible image steganography of encrypted image based on image interpolation and difference histogram shift

Cited by 11 publications

References 17 publications

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

A Huffman code LSB based image steganography technique using multi-level encryption and achromatic component of an image

SIHNet: A safe image hiding method with less information leaking

An image steganography using improved hyper-chaotic Henon map and fractal Tromino

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