IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i8p1764-d1117954.html
   My bibliography  Save this article

Capacity-Raising Reversible Data Hiding Using Empirical Plus–Minus One in Dual Images

Author

Listed:
  • Cheng-Ta Huang

    (International Bachelor Program in Informatics, Yuan Ze University, Taoyuan 32003, Taiwan
    Department of Information Management, Yuan Ze University, Taoyuan 32003, Taiwan)

  • Chi-Yao Weng

    (Department of Computer Science and Artificial Intelligence, National Pingtung University, Pingtung 90003, Taiwan)

  • Njabulo Sinethemba Shongwe

    (International Bachelor Program in Informatics, Yuan Ze University, Taoyuan 32003, Taiwan)

Abstract

Electronic records of a patient’s health history are often shared among healthcare providers, and patient data must be kept secure to maintain the privacy of patients. One way of doing this is through data hiding, and this paper demonstrates a scheme to achieve this. This paper proposes a capacity-raising reversible data-hiding scheme using an empirical rules table in dual images. The aim of this research is to avoid drawing awareness to the transmission of information by providing a steganographic technique capable of embedding high-capacity data into an image while maintaining the good quality of the image. To hide the secret message(s), a rules table containing 13 entries is presented. This rules table is extendable to a table of up to 262,133 entries (with each entry containing one distinct character) that are related to the 13 entries in terms of the rules. The rules of this table are used during the embedding and extraction procedures. In the proposed method, 512 × 512 images are divided into 1 × 2 blocks where adjacent pixels are represented using x and y for both embedding and extraction, respectively. Recovery of the cover image from the stego image is also achievable during the extraction process. Conducted experiments show that the proposed method has an average pixel-to-signal noise ratio of 52.65 dB, which is higher than that achieved with the methods discussed in this paper. Additionally, the proposed method can embed a wider range of characters (depending on the image size) as compared to the rest of the methods, hence its high embedding capacity of 4.25 bpp. The proposed method can also withstand security attacks such as RS, pixel value difference, entropy, and chi-square attacks. The proposed method is also undetectable under visual attack analyses such as the difference histogram, pixel difference histogram, and visual inspection. Based on the higher embedding capacity, pixel-to-signal noise ratio, the ability of this method to be undetected under visual attack analysis, and the ability of this method to withstand security attacks, it can be concluded that the proposed method is superior to the other methods.

Suggested Citation

  • Cheng-Ta Huang & Chi-Yao Weng & Njabulo Sinethemba Shongwe, 2023. "Capacity-Raising Reversible Data Hiding Using Empirical Plus–Minus One in Dual Images," Mathematics, MDPI, vol. 11(8), pages 1-27, April.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1764-:d:1117954
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/8/1764/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/8/1764/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaoyuan Wang & Xinrui Zhang & Meng Gao & Yuanze Tian & Chunhua Wang & Herbert Ho-Ching Iu, 2023. "A Color Image Encryption Algorithm Based on Hash Table, Hilbert Curve and Hyper-Chaotic Synchronization," Mathematics, MDPI, vol. 11(3), pages 1-18, January.
    2. Dong Han & Zhen Li & Mengyu Wang & Chang Xu & Kashif Sharif, 2023. "Privacy Preservation Authentication: Group Secret Handshake with Multiple Groups," Mathematics, MDPI, vol. 11(3), pages 1-11, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dan He & Zhanchuan Cai, 2024. "Reversible Data Hiding for Color Images Using Channel Reference Mapping and Adaptive Pixel Prediction," Mathematics, MDPI, vol. 12(4), pages 1-17, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hairong Lin & Chunhua Wang & Fei Yu & Jingru Sun & Sichun Du & Zekun Deng & Quanli Deng, 2023. "A Review of Chaotic Systems Based on Memristive Hopfield Neural Networks," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    2. Zizhao Xie & Jingru Sun & Yiping Tang & Xin Tang & Oluyomi Simpson & Yichuang Sun, 2023. "A K-SVD Based Compressive Sensing Method for Visual Chaotic Image Encryption," Mathematics, MDPI, vol. 11(7), pages 1-20, March.
    3. Mingxu Wang & Xianping Fu & Xiaopeng Yan & Lin Teng, 2024. "A New Chaos-Based Image Encryption Algorithm Based on Discrete Fourier Transform and Improved Joseph Traversal," Mathematics, MDPI, vol. 12(5), pages 1-19, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:11:y:2023:i:8:p:1764-:d:1117954. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.