Approach to the selection of the best cover image for information embedding in JPEG images based on the principles of the optimality

Evsutin, Oleg; Kokurina, Anna; Meshcheryakov, Roman

doi:10.1080/12460125.2018.1460163

Cited by 13 publications

(4 citation statements)

References 13 publications

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“…Currently, there exist a variety of cover selection techniques utilized in the field of steganography. These techniques encompass different methodologies, such as empirical selection based on changeable DCT (discrete cosine transform) coefficients [13], visual quality assessment [14], ratio of similar blocks [15], content complexity, and texture regions [16,17]. However, it is important to acknowledge that these empirical approaches do not demonstrate optimal undetectability when subjected to steganalysis.…”

Section: Cover Selection Schemesmentioning

confidence: 99%

Diversified Cover Selection for Image Steganography

Li,

Guo,

Qin

2023

Symmetry

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This paper proposes a new cover selection method for steganography. We focus on the scenario that the available images for selection contain diversified sources, i.e., nature images and metaverse images. For the scenario, we design a targeted strategy to evaluate the suitability for steganography of a candidate image, which selects images according to the undetectability against steganalytic tools symmetrically. Firstly, steganalytic features of the candidate images are extracted. Then, the features are fed on a steganalytic classifier, and the possibility of carrying secret data is calculated for cover selection. As a result, the selected images are the best candidates to resist steganalysis. Experimental results show that our method performs better than existing cover selection schemes when checked by steganalytic tools.

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Section: Cover Selection Schemesmentioning

confidence: 99%

Diversified Cover Selection for Image Steganography

Li,

Guo,

Qin

2023

Symmetry

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“…Since text files do not include a large amount of redundant data, they are used rarely in steganography; also audio and video are complicated to apply. Therefore the image is the best cover for hiding information [5]. An efficient steganography method should provide invisibility or perceptual transparency, high hiding capacity, robustness (i.e.…”

Section: ‫باستخدام‬ ‫الفهضى‬ ‫على‬ ‫القائمة‬ ‫الملهنة‬ ‫الصهر‬ ‫إخفاء‬ ‫طريقة‬ ‫األبعاد‬ ‫ثالثية‬ ‫القط‬ ‫خريطة‬ ‫حميد‬ ‫مجيد‬ ‫اب‬ ‫سر‬ mentioning

confidence: 99%

Chaos-based Color Image Steganography Method Using 3 D Cat Map

Hameed

Ali

Al-Khafaji

et al. 2021

eijs

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Steganography is a technique to hide a secret message within a different multimedia carrier so that the secret message cannot be identified. The goals of steganography techniques include improvements in imperceptibility, information hiding, capacity, security, and robustness. In spite of numerous secure methodologies that have been introduced, there are ongoing attempts to develop these techniques to make them more secure and robust. This paper introduces a color image steganographic method based on a secret map, namely 3-D cat. The proposed method aims to embed data using a secure structure of chaotic steganography, ensuring better security. Rather than using the complete image for data hiding, the selection of the image band and pixel coordination is adopted, using the 3D map that produces irregular outputs for embedding a secret message randomly in the least significant bit (LSB) of the cover image. This increases the complexity encountered by the attackers. The performance of the proposed method was evaluated and the results reveal that the proposed method provides a high level of security through defeating various attacks, such as statistical attacks, with no detectable distortion in the stego-image. Comparison results ensure that the proposed method surpasses other existing steganographic methods regarding the Mean Square Error (MSE) and Peak Signal-to-Noise Ratio(PSNR).

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“…Then the images with a larger number of changeable DCT coefficients and higher quality factor are selected as covers for secret data carrying. In [19], the JPEG images with high visual quality (such as high quality factor) are regarded as suitable covers for embedding. The authors suggested that the images with poor quality not only negatively affect the capacity but also provoke special attention.…”

Section: Related Workmentioning

confidence: 99%

Towards Improved Steganalysis: When Cover Selection is Used in Steganography

Wang

Zhang

2019

IEEE Access

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This paper proposes an improved steganalytic method when cover selection is used in steganography. We observed that the covers selected by existing cover selection methods normally have different characteristics from normal ones, and propose a steganalytic method to capture such differences. As a result, the detection accuracy of steganalysis is increased. In our method, we consider a number of images collected from one or more target (suspected but not known) users, and use an unsupervised learning algorithm such as k-means to adapt the performance of a pre-trained classifier towards the cover selection operation of the target user(s). The adaptation is done via pseudo-labels from the suspected images themselves, thus allowing the retrained classifier more aligned with the cover selection operation of the target user(s). We give experimental results to show that our method can indeed help increase the detection accuracy, especially when the percentage of stego images is between 0.3 and 0.7. INDEX TERMS Cover selection, steganography, steganalysis, clustering. communication engineering, in 2003, from Xi'an Jiaotong University, China. Since November 2017, he has been a Professor of cyber security with the University of Kent, U.K., leading the university wide Kent Interdisciplinary Research Centre in Cyber Security (KirCCS), a U.K. government recognized Academic Centre of Excellence in Cyber Security Research (ACE-CSR). He has published over 100 scientific articles with two Best Paper Awards. His research interests include cyber security, human-computer interface, multimedia computing, digital forensics, and cybercrime. XINPENG ZHANG (M'11) received the B.S. degree in computational mathematics from Jilin University, China, in 1995, and the M.E. and Ph.D. degrees in communication and information system from Shanghai University, China, in 2001 and 2004, respectively. Since 2004, he has been with the faculty of the School of Communication and Information Engineering, Shanghai University, where he is currently a Professor. His research interests include information hiding, image processing, and digital forensics. He has published over 200 articles in these areas.

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Approach to the selection of the best cover image for information embedding in JPEG images based on the principles of the optimality

Cited by 13 publications

References 13 publications

Diversified Cover Selection for Image Steganography

Diversified Cover Selection for Image Steganography

Chaos-based Color Image Steganography Method Using 3 D Cat Map

Towards Improved Steganalysis: When Cover Selection is Used in Steganography

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