Jiajun Liu¹, Lina Tan^1,*, Zhili Zhou², Weijin Jiang¹, Yi Li¹, Peng Chen¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3221-3240, 2024, DOI:10.32604/cmc.2024.054542 - 18 November 2024

Abstract Many existing coverless steganography methods establish a mapping relationship between cover images and hidden data. One issue with these methods is that as the steganographic capacity increases, the number of images stored in the database grows exponentially. This makes it challenging to build and manage a large image database. To improve the image library utilization and anti-attack capability of the steganography system, we propose an efficient coverless scheme based on dynamically matched substrings. We utilize You Only Look Once (YOLO) for selecting optimal objects and create a mapping dictionary between these objects and scrambling factors.… More >

Pengbiao Zhao¹, Qi Zhong², Jingxue Chen¹, Xiaopei Wang³, Zhen Qin¹, Erqiang Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 331-352, 2024, DOI:10.32604/cmes.2024.050148 - 20 August 2024

Abstract Information steganography has received more and more attention from scholars nowadays, especially in the area of image steganography, which uses image content to transmit information and makes the existence of secret information undetectable. To enhance concealment and security, the Steganography without Embedding (SWE) method has proven effective in avoiding image distortion resulting from cover modification. In this paper, a novel encrypted communication scheme for image SWE is proposed. It reconstructs the image into a multi-linked list structure consisting of numerous nodes, where each pixel is transformed into a single node with data and pointer domains.… More >

Al Hussien Seddik Saad¹, Mohammed S. Reda², Gamal M. Behery², Ahmed A. El-harby², Mohammed Baz³, Mohamed Abouhawwash^4,5,*, Ahmed Ismail Ebada⁶

Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 125-138, 2023, DOI:10.32604/iasc.2023.032084 - 05 February 2024

Abstract The trend of digital information transformation has become a topic of interest. Many data are threatening; thus, protecting such data from attackers is considered an essential process. Recently, a new methodology for data concealing has been suggested by researchers called coverless steganography. Coverless steganography can be accomplished either by building an image database to match its image subblocks with the secret message to obtain the stego image or by generating an image. This paper proposes a coverless image steganography system based on pure image generation using secret message bits with a capacity higher than the… More >

Al-Hussien Seddik¹, Mohammed Salah², Gamal Behery², Ahmed El-harby², Ahmed Ismail Ebada², Sokea Teng³, Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5087-5103, 2023, DOI:10.32604/cmc.2023.035364 - 28 December 2022

Abstract The ability of any steganography system to correctly retrieve the secret message is the primary criterion for measuring its efficiency. Recently, researchers have tried to generate a new natural image driven from only the secret message bits rather than using a cover to embed the secret message within it; this is called the stego image. This paper proposes a new secured coverless steganography system using a generative mathematical model based on semi Quick Response (QR) code and maze game image generation. This system consists of two components. The first component contains two processes, encryption process,… More >

Runze Li¹, Jiaohua Qin^1,*, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1571-1583, 2022, DOI:10.32604/cmc.2022.029378 - 18 May 2022

Abstract Most existing coverless video steganography algorithms use a particular video frame for information hiding. These methods do not reflect the unique sequential features of video carriers that are different from image and have poor robustness. We propose a coverless video steganography method based on frame sequence perceptual distance mapping. In this method, we introduce Learned Perceptual Image Patch Similarity (LPIPS) to quantify the similarity between consecutive video frames to obtain the sequential features of the video. Then we establish the relationship map between features and the hash sequence for information hiding. In addition, the MongoDB More >

Lin Xiang¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 899-914, 2021, DOI:10.32604/iasc.2021.017720 - 01 July 2021

Abstract Recently, researchers have shown that coverless information hiding technology can effectively resist the existing steganalysis tools. However, the robustness of existing coverless text information hiding methods is generally poor. To solve this problem, we propose a robust text coverless information hiding method based on multi-index. Firstly, the sender segment the secret information into several keywords. Secondly, we transform keywords into keyword IDs by the word index table and introduce a random increment factor to control. Then, search all texts containing the keyword ID in the big data text, and use the robust text search algorithm More >

Al Hussien Seddik Saad^1,*, M. S. Mohamed^2,3, E. H. Hafez⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2077-2091, 2021, DOI:10.32604/cmc.2021.015329 - 05 February 2021

Abstract Current image steganography methods are working by assigning an image as a cover file then embed the payload within it by modifying its pixels, creating the stego image. However, the left traces that are caused by these modifications will make steganalysis algorithms easily detect the hidden payload. A coverless data hiding concept is proposed to solve this issue. Coverless does not mean that cover is not required, or the payload can be transmitted without a cover. Instead, the payload is embedded by cover generation or a secret message mapping between the cover file and the… More >

Ning Wu^1,2, Yi Yang^1,*, Lian Li¹, Zhongliang Yang³, Poli Shang⁴, Weibo Ma⁵, Zhenru Liu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1035-1048, 2020, DOI:10.32604/cmes.2020.010450 - 21 August 2020

Abstract In the field of information hiding, text is less redundant, which leads to less space to hide information and challenging work for researchers. Based on the Markov chain model, this paper proposes an improved evaluation index and onebit embedding coverless text steganography method. In the steganography process, this method did not simply take the transition probability as the optimization basis of the steganography model, but combined it with the sentence length in the corresponding nodes in the model to gauge sentence quality. Based on this, only two optimal conjunctions of the current words are retained More >

Yun Tan¹, Jiaohua Qin^{1, *}, Hao Tang², Xuyu Xiang¹, Ling Tan², Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1797-1817, 2020, DOI:10.32604/cmc.2020.010802 - 30 June 2020

Abstract With the development of the internet of medical things (IoMT), the privacy protection problem has become more and more critical. In this paper, we propose a privacy protection scheme for medical images based on DenseNet and coverless steganography. For a given group of medical images of one patient, DenseNet is used to regroup the images based on feature similarity comparison. Then the mapping indexes can be constructed based on LBP feature and hash generation. After mapping the privacy information with the hash sequences, the corresponding mapped indexes of secret information will be packed together with More >

Yuanjing Luo¹, Jiaohua Qin^{1, *}, Xuyu Xiang¹, Yun Tan¹, Zhibin He¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1281-1295, 2020, DOI:10.32604/cmc.2020.010867 - 10 June 2020

Abstract To resist the risk of the stego-image being maliciously altered during transmission, we propose a coverless image steganography method based on image segmentation. Most existing coverless steganography methods are based on whole feature mapping, which has poor robustness when facing geometric attacks, because the contents in the image are easy to lost. To solve this problem, we use ResNet to extract semantic features, and segment the object areas from the image through Mask RCNN for information hiding. These selected object areas have ethical structural integrity and are not located in the visual center of the… More >