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SecECG: secure data hiding approach for ECG signals in smart healthcare applications

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Abstract

Rapid development of communication technologies and Point of Care (POC) services has encouraged the sharing of digital biomedical records through the open network to achieve remote health assistance. These medical records contain sensitive and confidential information about patients. Preserving this data from illegal distribution and alteration during transmission is a major challenge. To secure biomedical signals, the encryption-based non-blind watermarking method is introduced in this article. A robust and secure technique is established for embedding a watermark into an ECG signal using the Contourlet Transform and Multi-resolution SVD. In the initial phase, the mark image is ciphered using chaotic shift transform and modified henon map-based encryption technique to improve the security of the proposed work. The encrypted watermark is then inserted into the higher frequency coefficients of the ECG signal to prevent ownership issues and ensure copyright protection. The standard ECG MIT-BIH and PTB Diagnostic ECG datasets are utilized to evaluate the suggested algorithm. The suggested approach is compared to the current literature, and the results reveal a maximum improvement in robustness of 28.98 %. This method yields promising outcomes in terms of stability, invisibility, and safety. The experimental results on visual quality and resilience suggest that the proposed approaches keep the high resolution of watermarked images and are remarkably resilient to a wide range of conventional attacks.

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Data Availability

The datasets generated during and/or analyzed during the current study are available online [44] and [45].

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Authors and Affiliations

  1. Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Jyoti Rani, Ashima Anand & Shivendra Shivani

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  1. Jyoti Rani
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  2. Ashima Anand
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  3. Shivendra Shivani
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Correspondence to Ashima Anand.

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Rani, J., Anand, A. & Shivani, S. SecECG: secure data hiding approach for ECG signals in smart healthcare applications. Multimed Tools Appl 83, 42885–42905 (2024). https://doi.org/10.1007/s11042-023-17049-3

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  • DOI: https://doi.org/10.1007/s11042-023-17049-3

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