Abstract
Zero-watermarking (ZW) presents a promising approach for safeguarding image copyright, as it does not alter the original image, a crucial feature for preserving the integrity of medical and high-fidelity visual data. Nevertheless, numerous existing ZW techniques are susceptible to geometric distortions and signal-processing attacks, thereby offering limited protection for ownership and licensing information. This paper proposes a robust and secure zero-watermarking scheme for medical and natural color images that jointly supports ownership authentication and license verification. The method combines entropy- and SIFT-based sub-region selection, DWT-DCT feature extraction, and XOR fusion between robust features and an Arnold-scrambled logo, followed by an ElGamal-style signcryption of the resulting share. Multiple local zero-watermarks are registered in a Certification Authority (CA), enabling global watermark reconstruction without altering the original image. Experimental results show that the normalized correlation (NC) between the recovered and watermark remains above 0.99 under various geometric and non-geometric attacks, confirming the robustness of the scheme. In addition, the signcryption module incurs low computational overhead, with both the encryption and joint decryption–verification processes requiring approximately 8.5 milliseconds. This overhead is small compared with the transform-based processing time and yields a favorable trade-off between enhanced cryptographic protection of ownership/license records and the computational efficiency required for practical medical imaging and large-scale copyright management systems.
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Data availability
The medical images used in this study were randomly selected from the publicly available The Cancer Imaging Archive (TCIA) repository and can be accessed at: [https://nbia.cancerimagingarchive.net/nbia-search/](https:/nbia.cancerimagingarchive.net/nbia-search) . In addition, three standard color images were obtained from the widely used USC-SIPI image database, available at: [http://sipi.usc.edu/database/](http:/sipi.usc.edu/database) . All datasets analysed during the current study are publicly available from the above repositories and were used in accordance with their respective terms of use.No additional permission or informed consent is required to publish or reuse the images used in this study. The medical images were obtained from The Cancer Imaging Archive (TCIA), which provides publicly available datasets that have been fully de-identified in accordance with applicable ethical and legal standards, including HIPAA. Therefore, the images do not contain any personally identifiable information. The color images were taken from the USC-SIPI standard image database, which is a publicly available benchmark dataset widely used for research and reproducibility purposes. Consequently, all images used in this study can be safely employed for reproducibility without ethical or consent-related restrictions.
Code availability
The core implementation of the proposed zero-watermarking framework is publicly available at: https://github.com/hungpt-mta/zero-watermarking-core. The provided code is sufficient to run the benchmarking procedures described in this paper. The experimental datasets are not redistributed within the code repository, but are publicly available from The Cancer Imaging Archive (TCIA) and the USC-SIPI image database, and can be obtained directly from their respective sources.
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Funding
This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 04/2025/TN.
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Ta Minh Thanh: Supervision, Investigation, Conceptualization, Methodology. Pham Thai Hung: Code, Data curation, Visualization, Investigation, Software.
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Hung, P.T., Thanh, T.M. A robust zero-watermarking and signcryption scheme for image copyright protection and license verification. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38991-w
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DOI: https://doi.org/10.1038/s41598-026-38991-w
