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<p>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.</p>

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A robust zero-watermarking and signcryption scheme for image copyright protection and license verification

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月14日

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  • Pham Thai Hung,
  • Ta Minh Thanh

摘要

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.