Yixin Tang^1,2, Minqing Zhang^1,2,3,*, Peizheng Lai^1,2, Ya Yue^1,2, Fuqiang Di^1,2,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5733-5750, 2025, DOI:10.32604/cmc.2025.064901 - 30 July 2025

Abstract Traditional steganography conceals information by modifying cover data, but steganalysis tools easily detect such alterations. While deep learning-based steganography often involves high training costs and complex deployment. Diffusion model-based methods face security vulnerabilities, particularly due to potential information leakage during generation. We propose a fixed neural network image steganography framework based on secure diffusion models to address these challenges. Unlike conventional approaches, our method minimizes cover modifications through neural network optimization, achieving superior steganographic performance in human visual perception and computer vision analyses. The cover images are generated in an anime style using state-of-the-art diffusion More >

Nagaraj V. Dharwadkar^*

Journal of Information Hiding and Privacy Protection, Vol.7, pp. 1-31, 2025, DOI:10.32604/jihpp.2025.060898 - 27 March 2025

Abstract Steganography, the art of concealing information within innocuous mediums, has been practiced for centuries and continues to evolve with advances in digital technology. In the modern era, steganography has become an essential complementary tool to cryptography, offering an additional layer of security, stealth, and deniability in digital communications. With the rise of cyber threats such as hacking, malware, and phishing, it is crucial to adopt methods that protect the confidentiality and integrity of data. This review focuses specifically on text-in-image steganography, exploring a range of techniques, including Least Significant Bit (LSB), Pixel Value Differencing (PVD),… More >

Xiang Zhang^1,2,*, Shenyan Han^1,2, Wenbin Huang^1,2, Daoyong Fu^1,2

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1149-1171, 2025, DOI:10.32604/cmc.2025.060876 - 26 March 2025

Abstract Generative image steganography is a technique that directly generates stego images from secret information. Unlike traditional methods, it theoretically resists steganalysis because there is no cover image. Currently, the existing generative image steganography methods generally have good steganography performance, but there is still potential room for enhancing both the quality of stego images and the accuracy of secret information extraction. Therefore, this paper proposes a generative image steganography algorithm based on attribute feature transformation and invertible mapping rule. Firstly, the reference image is disentangled by a content and an attribute encoder to obtain content features… More >

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 >

Murad Njoum^1,2,*, Rossilawati Sulaiman¹, Zarina Shukur¹, Faizan Qamar¹

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 183-211, 2024, DOI:10.32604/cmc.2024.050090 - 15 October 2024

Abstract Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data. This property makes it difficult for steganalysts’ powerful data extraction tools to detect the hidden data and ensures high-quality stego image generation. However, using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical equations. In addition, these numbers may cluster in certain ranges. The hidden data in these clustered pixels will reduce the image quality, which steganalysis tools can detect. Therefore, this paper proposes a… More >

Zinah Khalid Jasim Jasim^*, Sefer Kurnaz^*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4643-4662, 2024, DOI:10.32604/cmc.2024.055195 - 12 September 2024

Abstract This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization (ACO) algorithm. Image steganography, a technique of embedding hidden information in digital photographs, should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect. The contemporary methods of steganography are at best a compromise between these two. In this paper, we present our approach, entitled Ant Colony Optimization (ACO)-Least Significant Bit (LSB), which attempts to optimize the capacity in steganographic embedding. The approach makes use… More >

Da-Chun Wu^*, Zong-Nan Shih

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 353-383, 2024, DOI:10.32604/cmes.2024.050813 - 20 August 2024

Abstract A new steganographic method by pixel-value differencing (PVD) using general quantization ranges of pixel pairs’ difference values is proposed. The objective of this method is to provide a data embedding technique with a range table with range widths not limited to powers of 2, extending PVD-based methods to enhance their flexibility and data-embedding rates without changing their capabilities to resist security attacks. Specifically, the conventional PVD technique partitions a grayscale image into 1 × 2 non-overlapping blocks. The entire range [0, 255] of all possible absolute values of the pixel pairs’ grayscale differences in the… 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 >

Abdullah Alenizi¹, Mohammad Sajid Mohammadi², Ahmad A. Al-Hajji², Arshiya Sajid Ansari^1,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2463-2494, 2024, DOI:10.32604/cmc.2024.051826 - 15 August 2024

Abstract Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item. From ancient times to the present, the security of secret or vital information has always been a significant problem. The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest. Therefore, several approaches, including steganography, have been developed by researchers over time to enable safe data transit. In this review, we have discussed image steganography based on Discrete Cosine Transform (DCT) algorithm, etc. We have also discussed image steganography based… More >

AFM Zainul Abadin^1,2,*, Rossilawati Sulaiman¹, Mohammad Kamrul Hasan¹

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3139-3171, 2024, DOI:10.32604/cmc.2024.050834 - 15 August 2024

Abstract Image steganography is one of the prominent technologies in data hiding standards. Steganographic system performance mostly depends on the embedding strategy. Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image. The randomization strategies in data embedding techniques may utilize random domains, pixels, or region-of-interest for concealing secrets into a cover image, preventing information from being discovered by an attacker. The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility, but it is challenging. A systematic approach is More >