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  • Open Access

    ARTICLE

    Interpolation-Based Reversible Data Hiding in Encrypted Audio with Scalable Embedding Capacity

    Yuan-Yu Tsai1,*, Alfrindo Lin1, Wen-Ting Jao1, Yi-Hui Chen2,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 681-697, 2025, DOI:10.32604/cmc.2025.064370 - 09 June 2025

    Abstract With the rapid expansion of multimedia data, protecting digital information has become increasingly critical. Reversible data hiding offers an effective solution by allowing sensitive information to be embedded in multimedia files while enabling full recovery of the original data after extraction. Audio, as a vital medium in communication, entertainment, and information sharing, demands the same level of security as images. However, embedding data in encrypted audio poses unique challenges due to the trade-offs between security, data integrity, and embedding capacity. This paper presents a novel interpolation-based reversible data hiding algorithm for encrypted audio that achieves… More >

  • Open Access

    ARTICLE

    Edge-Based Data Hiding and Extraction Algorithm to Increase Payload Capacity and Data Security

    Hanan Hardan1,*, Osama A. Khashan2,*, Mohammad Alshinwan1

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1681-1710, 2025, DOI:10.32604/cmc.2025.061659 - 09 June 2025

    Abstract This study introduces an Edge-Based Data Hiding and Extraction Algorithm (EBDHEA) to address the problem of data embedding in images while preserving robust security and high image quality. The algorithm produces three classes of pixels from the pixels in the cover image: edges found by the Canny edge detection method, pixels arising from the expansion of neighboring edge pixels, and pixels that are neither edges nor components of the neighboring edge pixels. The number of Least Significant Bits (LSBs) that are used to hide data depends on these classifications. Furthermore, the lossless compression method, Huffman… More >

  • Open Access

    ARTICLE

    FuzzyStego: An Adaptive Steganographic Scheme Using Fuzzy Logic for Optimizing Embeddable Areas in Spatial Domain Images

    Mardhatillah Shevy Ananti1, Adifa Widyadhani Chanda D’Layla1, Ntivuguruzwa Jean De La Croix1,2, Tohari Ahmad1,*

    CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1031-1054, 2025, DOI:10.32604/cmc.2025.061246 - 09 June 2025

    Abstract In the evolving landscape of secure communication, steganography has become increasingly vital to secure the transmission of secret data through an insecure public network. Several steganographic algorithms have been proposed using digital images with a common objective of balancing a trade-off between the payload size and the quality of the stego image. In the existing steganographic works, a remarkable distortion of the stego image persists when the payload size is increased, making several existing works impractical to the current world of vast data. This paper introduces FuzzyStego, a novel approach designed to enhance the stego… More >

  • Open Access

    ARTICLE

    A Novel Data-Annotated Label Collection and Deep-Learning Based Medical Image Segmentation in Reversible Data Hiding Domain

    Lord Amoah1,2, Jinwei Wang1,2,3,*, Bernard-Marie Onzo1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1635-1660, 2025, DOI:10.32604/cmes.2025.063992 - 30 May 2025

    Abstract Medical image segmentation, i.e., labeling structures of interest in medical images, is crucial for disease diagnosis and treatment in radiology. In reversible data hiding in medical images (RDHMI), segmentation consists of only two regions: the focal and nonfocal regions. The focal region mainly contains information for diagnosis, while the nonfocal region serves as the monochrome background. The current traditional segmentation methods utilized in RDHMI are inaccurate for complex medical images, and manual segmentation is time-consuming, poorly reproducible, and operator-dependent. Implementing state-of-the-art deep learning (DL) models will facilitate key benefits, but the lack of domain-specific labels… More >

  • Open Access

    ARTICLE

    Robust Reversible Watermarking Technique Based on Improved Polar Harmonic Transform

    Muath AlShaikh*

    Computer Systems Science and Engineering, Vol.49, pp. 435-453, 2025, DOI:10.32604/csse.2025.062432 - 13 May 2025

    Abstract Many existing watermarking approaches aim to provide a Robust Reversible Data Hiding (RRDH) method. However, most of these approaches degrade under geometric and non-geometric attacks. This paper presents a novel RRDH approach using Polar Harmonic Fourier Moments (PHFMs) and linear interpolation. The primary objective is to enhance the robustness of the embedded watermark and improve the imperceptibility of the watermarked image. The proposed method leverages the high-fidelity and anti-geometric transformation properties of PHFMs. The image is transformed into the frequency domain of RRDH, after which compensation data is embedded using a two-dimensional RDH scheme. Linear… More >

  • Open Access

    ARTICLE

    Reversible Data Hiding Algorithm in Encrypted Images Based on Adaptive Median Edge Detection and Ciphertext-Policy Attribute-Based Encryption

    Zongbao Jiang, Minqing Zhang*, Weina Dong, Chao Jiang, Fuqiang Di

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1123-1155, 2024, DOI:10.32604/cmc.2024.055120 - 15 October 2024

    Abstract With the rapid advancement of cloud computing technology, reversible data hiding algorithms in encrypted images (RDH-EI) have developed into an important field of study concentrated on safeguarding privacy in distributed cloud environments. However, existing algorithms often suffer from low embedding capacities and are inadequate for complex data access scenarios. To address these challenges, this paper proposes a novel reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and ciphertext-policy attribute-based encryption (CP-ABE). This proposed algorithm enhances the conventional median edge detection (MED) by incorporating dynamic variables to improve pixel prediction… More >

  • Open Access

    ARTICLE

    Pairwise Reversible Data Hiding for Medical Images with Contrast Enhancement

    Isaac Asare Boateng1,2,*, Lord Amoah2, Isogun Toluwalase Adewale3

    Journal of Information Hiding and Privacy Protection, Vol.6, pp. 1-19, 2024, DOI:10.32604/jihpp.2024.051354 - 24 June 2024

    Abstract Contrast enhancement in medical images has been vital since the prevalence of image representations in healthcare. In this research, the PRDHMCE (pairwise reversible data hiding for medical images with contrast enhancement) algorithm is proposed as an automatic contrast enhancement (CE) method for medical images based on region of interest (ROI) and non-region of interest (NROI). The PRDHMCE algorithm strategically enhances the ROI after segmentation using histogram stretching and data embedding. An initial histogram evaluation compares histogram bins with their neighbours to select the bin with the maximum pixel count. The selected bin is set as More >

  • Open Access

    ARTICLE

    Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding

    Kai Gao1, Chin-Chen Chang1,*, Chia-Chen Lin2,*

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 813-833, 2024, DOI:10.32604/csse.2024.038308 - 20 May 2024

    Abstract Reversible data hiding is a confidential communication technique that takes advantage of image file characteristics, which allows us to hide sensitive data in image files. In this paper, we propose a novel high-fidelity reversible data hiding scheme. Based on the advantage of the multipredictor mechanism, we combine two effective prediction schemes to improve prediction accuracy. In addition, the multihistogram technique is utilized to further improve the image quality of the stego image. Moreover, a model of the grouped knapsack problem is used to speed up the search for the suitable embedding bin in each sub-histogram. More >

  • Open Access

    ARTICLE

    Coverless Image Steganography System Based on Maze Game Generation

    Al Hussien Seddik Saad1, Mohammed S. Reda2, Gamal M. Behery2, Ahmed A. El-harby2, Mohammed Baz3, Mohamed Abouhawwash4,5,*, 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 >

  • Open Access

    ARTICLE

    High-Imperceptibility Data Hiding Scheme for JPEG Images Based on Direction Modification

    Li Liu1, Jing Li1, Yingchun Wu1, Chin-Chen Chang2,*, Anhong Wang1

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1415-1432, 2023, DOI:10.32604/csse.2023.040039 - 28 July 2023

    Abstract Data hiding (DH) is an important technology for securely transmitting secret data in networks, and has increasing become a research hotspot throughout the world. However, for Joint photographic experts group (JPEG) images, it is difficult to balance the contradiction among embedded capacity, visual quality and the file size increment in existing data hiding schemes. Thus, to deal with this problem, a high-imperceptibility data hiding for JPEG images is proposed based on direction modification. First, this proposed scheme sorts all of the quantized discrete cosine transform (DCT) block in ascending order according to the number of… More >

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